Research questions

The primary goal of this study was a comparison of grab sample, stomach tubing and feces to understand how different sampling methods will effect the microbial communities found in samples. The current “gold standard” for surveying the rumen microbiome is with a grab sample from the rument that contains both liquid and solid particles. On a commercial dairy, fecal sampling is easy to do. Stomach tube could be done with a little more time. If a fecal sample is not representative of the stomach tube, then there is no sense doing the fecal sampling as a monitor for rumen conditions. In reality, if the stomach tube and the fecal sample do not reflect the grab sample (gold standard) then neither would be used to monitor rumen microbial health (populations).

We seek to answer the following questions:

  • How are sample types different?
    • Alpha diversity (richness and evenness)
    • Beta diversity
    • Differentially abundant and differentially variable ASVs.
  • What ASVs are shared between samples of the same type.

A secondary question is the decomposition of the grab sample (liquid strained & solid). The grab sample was separated into liquid strained and solid particulate by pressing the grab sample through cheese cloth to get liquid strained and solid particulate. We will have a closer look at what communites are in what parts of the grab sample.

Other Questions of interest:

  • Have a look at the feed microbiome from the two different kits (TMR_plant_kit and TMR_fecal_kit) to see if there is a relationship between the feed and sample type.
  • Typically, the liquid unstrained is what we would collect from a rumen fistulated cow and then transfaunate using a stomach tube into a sick cow that is experiencing simple indigestion. How does the microbial population of the liquid unstrained compared with the grab sample, liquid strained, and solid? That is to say, when we transfaunate what mircrobial populations are we transfering.
  • How constant is the rumen population over time in the same animal?
    • This can’t be tested as we only have one sample per day and thus can estimate variations on a day
  • There is one Jersey in the study is her microbiome different from the holstiens?
    • We can’t really answer this as we only have an n=1

Note that prior to running DADA2 sequences were cleaned with kneaddata and then demuliplexed and primers trimmed with cuteadapt. Code for this is available at my GitHub Page

Running DADA2 to get ASVs and assign taxonomy.

This program infers exact amplicon sequence variants (ASVs) from amplicon data, resolving biological differences of even 1 or 2 nucleotides. This algorithum is prefered as DADA2 reports fewer false positive sequence variants than other methods report false OTUs. Note that this is a computationally expensive so its run on a cluster and then the R objects are read in.

First we will read in the data and trim ends where there is poor quality.

The next steps learn the error rates of the data and identifies unique sequences. These data are fed into the main dada2 algorithum that makes a table of ASVs. Reads are merged and chimerias removed prior to making the final ASV table. Taxaonomy was assined using the silva database.

Getting information out of DADA2 Objects.

Let’s check the sizes of the sequences as a way to determine contamination.

## 
##  221  223  226  227  229  230  231  232  237  246  251  252  253  254  255 
##    1    1    2    1    3    8    1    1    2    1    5  858 4510  131    6 
##  256  257  263  269  270  271  275  277  281  283  285  287  292  293  294 
##    1    1    2    7   24    2    1    1    1    1   12    1    7   26    1 
##  342  383 
##    1    1
## [1] 256.5

These sequences have a median length of 256.5 with most are less than 390bp. The sequences longer sequences may be the result of non-specific priming. We will look at this again after specific and thoughtful filtering. If long sequences remain after filtering we will look at them closer to make sure they are infact from bacterial origin.

Now we check the number of chimeras in the dataset.

## [1] 0.9795362

Here we see that 2.01% of the sequences were identified to be chimerias and were removed from the dataset. Next, we will have a look at the read stats.

##                            input filtered denoisedF denoisedR merged
## 282_Trim_R1.fastq.gz        9052     7645      7522      7410   6879
## 283_Trim_R1.fastq.gz       13464    11359     11216     11089  10503
## 284_Trim_R1.fastq.gz        9144     7769      7658      7584   7108
## 285_Trim_R1.fastq.gz        9372     7985      7856      7727   7211
## 286_Trim_R1.fastq.gz       11633     9828      9692      9605   9020
## 287_Trim_R1.fastq.gz        9598     8197      8048      7949   7420
## 288_Trim_R1.fastq.gz        5220     4431      4354      4290   4019
## 289_Trim_R1.fastq.gz        5475     4643      4578      4501   4235
## 290_Trim_R1.fastq.gz       11958    10168     10032      9968   9301
## 291_Trim_R1.fastq.gz        5232     4445      4382      4330   4063
## 292_Trim_R1.fastq.gz        9222     7816      7700      7586   7048
## 293_Trim_R1.fastq.gz        8496     7327      7225      7160   6789
## 294_Trim_R1.fastq.gz        5616     4744      4664      4594   4331
## 295_Trim_R1.fastq.gz        7305     6196      6095      6008   5601
## 296_Trim_R1.fastq.gz        8684     7346      7247      7115   6652
## 297_Trim_R1.fastq.gz        7593     6304      6213      6078   5683
## 298_Trim_R1.fastq.gz       11098     9374      9213      9087   8521
## 299_Trim_R1.fastq.gz        9184     7836      7704      7577   7100
## 300_Trim_R1.fastq.gz        8612     7226      7115      6969   6516
## 301_Trim_R1.fastq.gz        7719     6476      6345      6231   5827
## 302_Trim_R1.fastq.gz        6805     5725      5634      5572   5198
## 303_Trim_R1.fastq.gz        7157     6103      6008      5894   5509
## 304_Trim_R1.fastq.gz        9437     8116      7823      7844   6943
## 306_Trim_R1.fastq.gz        8613     7475      7359      7312   6933
## 307_Trim_R1.fastq.gz        5220     4588      4514      4482   4260
## 308_Trim_R1.fastq.gz        9229     7774      7643      7623   7145
## 309_Trim_R1.fastq.gz       12202    10326     10125     10016   9420
## 310_Trim_R1.fastq.gz        9933     8518      8388      8336   7893
## 311_Trim_R1.fastq.gz       13931    11779     11565     11480  10846
## 312_Trim_R1.fastq.gz        7955     6758      6643      6604   6191
## 314_Trim_R1.fastq.gz        6183     5271      5196      5116   4731
## 359_Trim_R1.fastq.gz       11088     9360      9236      9153   8597
## 360_Trim_R1.fastq.gz       11846    10163      9985      9881   9254
## 361_Trim_R1.fastq.gz       13308    11306     11124     11004  10307
## 362_Trim_R1.fastq.gz        9383     7936      7805      7761   7266
## 363_Trim_R1.fastq.gz        6851     5715      5612      5538   5182
## 365_Trim_R1.fastq.gz        6992     5982      5890      5824   5480
## 366_Trim_R1.fastq.gz        6330     5713      5597      5572   5234
## 367_Trim_R1.fastq.gz        6732     6075      5956      5948   5526
## 368_Trim_R1.fastq.gz        8080     7280      7123      7112   6699
## 369_Trim_R1.fastq.gz       16363    14678     14369     14329  13337
## 370_Trim_R1.fastq.gz       11504    10371     10027     10134   9326
## 371_Trim_R1.fastq.gz       11769    10494     10253     10253   9557
## 372_Trim_R1.fastq.gz       15193    13658     13372     13357  12485
## 373_Trim_R1.fastq.gz       14512    13010     12743     12711  11860
## 374_Trim_R1.fastq.gz       11580    10359     10154     10090   9456
## 375_Trim_R1.fastq.gz       12296    11085     10797     10768   9966
## 376_Trim_R1.fastq.gz       13002    11778     11529     11506  10744
## 378_Trim_R1.fastq.gz       13050    11829     11566     11509  10739
## 379_Trim_R1.fastq.gz       13484    11184     11022     10760   9935
## 380_Trim_R1.fastq.gz       12795    10698     10534     10299   9511
## 381_Trim_R1.fastq.gz       13125    11040     10841     10659   9902
## 382_Trim_R1.fastq.gz       21991    18506     18264     17908  16698
## 383_Trim_R1.fastq.gz        8923     7465      7362      7233   6745
## 384_Trim_R1.fastq.gz       12080    10234     10064      9874   9117
## 385_Trim_R1.fastq.gz        9747     8208      8072      7933   7441
## 386_Trim_R1.fastq.gz       16271    13550     13287     13095  12188
## 387_Trim_R1.fastq.gz       25059    21471     20099     19119  15561
## 388_Trim_R1.fastq.gz       13699    11576     11356     11247  10419
## 389_Trim_R1.fastq.gz       14755    12555     12069     12082  10761
## 390_Trim_R1.fastq.gz        2836     2461      2427      2377   2227
## 505_Trim_R1.fastq.gz        6303     5333      5231      5210   4914
## 506_Trim_R1.fastq.gz       10828     9075      8896      8819   8260
## 507_Trim_R1.fastq.gz        7388     6304      6214      6180   5849
## 508_Trim_R1.fastq.gz        4846     4195      4127      4087   3873
## 509_Trim_R1.fastq.gz       31810    27287     26782     26568  24933
## 510_Trim_R1.fastq.gz       17493    14980     14728     14579  13701
## 511_Trim_R1.fastq.gz       16696    14268     14037     13912  13125
## Fecal_kit_Trim_R1.fastq.gz  7136     6431      6213      6246   5847
## Plant_kit_Trim_R1.fastq.gz 10475     9326      9114      9144   8641
##                            nonchim
## 282_Trim_R1.fastq.gz          6771
## 283_Trim_R1.fastq.gz         10316
## 284_Trim_R1.fastq.gz          6997
## 285_Trim_R1.fastq.gz          7089
## 286_Trim_R1.fastq.gz          8842
## 287_Trim_R1.fastq.gz          7300
## 288_Trim_R1.fastq.gz          3946
## 289_Trim_R1.fastq.gz          4159
## 290_Trim_R1.fastq.gz          9108
## 291_Trim_R1.fastq.gz          3992
## 292_Trim_R1.fastq.gz          6894
## 293_Trim_R1.fastq.gz          6690
## 294_Trim_R1.fastq.gz          4234
## 295_Trim_R1.fastq.gz          5501
## 296_Trim_R1.fastq.gz          6513
## 297_Trim_R1.fastq.gz          5571
## 298_Trim_R1.fastq.gz          8348
## 299_Trim_R1.fastq.gz          6987
## 300_Trim_R1.fastq.gz          6354
## 301_Trim_R1.fastq.gz          5710
## 302_Trim_R1.fastq.gz          5085
## 303_Trim_R1.fastq.gz          5411
## 304_Trim_R1.fastq.gz          6777
## 306_Trim_R1.fastq.gz          6859
## 307_Trim_R1.fastq.gz          4205
## 308_Trim_R1.fastq.gz          7033
## 309_Trim_R1.fastq.gz          9302
## 310_Trim_R1.fastq.gz          7800
## 311_Trim_R1.fastq.gz         10718
## 312_Trim_R1.fastq.gz          6091
## 314_Trim_R1.fastq.gz          4646
## 359_Trim_R1.fastq.gz          8447
## 360_Trim_R1.fastq.gz          9124
## 361_Trim_R1.fastq.gz         10133
## 362_Trim_R1.fastq.gz          7114
## 363_Trim_R1.fastq.gz          5086
## 365_Trim_R1.fastq.gz          5373
## 366_Trim_R1.fastq.gz          5108
## 367_Trim_R1.fastq.gz          5396
## 368_Trim_R1.fastq.gz          6523
## 369_Trim_R1.fastq.gz         12909
## 370_Trim_R1.fastq.gz          9068
## 371_Trim_R1.fastq.gz          9325
## 372_Trim_R1.fastq.gz         12123
## 373_Trim_R1.fastq.gz         11506
## 374_Trim_R1.fastq.gz          9155
## 375_Trim_R1.fastq.gz          9677
## 376_Trim_R1.fastq.gz         10412
## 378_Trim_R1.fastq.gz         10388
## 379_Trim_R1.fastq.gz          9705
## 380_Trim_R1.fastq.gz          9308
## 381_Trim_R1.fastq.gz          9710
## 382_Trim_R1.fastq.gz         16323
## 383_Trim_R1.fastq.gz          6608
## 384_Trim_R1.fastq.gz          8923
## 385_Trim_R1.fastq.gz          7279
## 386_Trim_R1.fastq.gz         11864
## 387_Trim_R1.fastq.gz         14877
## 388_Trim_R1.fastq.gz         10229
## 389_Trim_R1.fastq.gz         10542
## 390_Trim_R1.fastq.gz          2189
## 505_Trim_R1.fastq.gz          4867
## 506_Trim_R1.fastq.gz          8152
## 507_Trim_R1.fastq.gz          5755
## 508_Trim_R1.fastq.gz          3833
## 509_Trim_R1.fastq.gz         24624
## 510_Trim_R1.fastq.gz         13462
## 511_Trim_R1.fastq.gz         12964
## Fecal_kit_Trim_R1.fastq.gz    5807
## Plant_kit_Trim_R1.fastq.gz    8562

This shows the library sizes of the samples and how many reads were removed at each step. There is 7.4796110^{5} cleaned reads that entered the DADA2 pipeline. We will now get read stats for the input ASVs.

## [1] 747961

We compare this to the read stats for the final libraries.

Making phyloseq object

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5607 taxa and 70 samples ]
## sample_data() Sample Data:       [ 70 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5607 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5607 tips and 5605 internal nodes ]

Cleaning data

Currently, we are starting with 5,607 ASVs from 70 samples

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5607 taxa and 68 samples ]
## sample_data() Sample Data:       [ 68 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5607 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5607 tips and 5605 internal nodes ]

First, we remove the kit samples to bring us down to 68 samples. We will look at these again later. We will also remove ASVs that aren’t present in any samples.

There was no empty samples or taxa which is what we want. Also, there was 16 ASVs that weren’t in any sample and were removed.

More cleaning of data

To start cleaning the data we will at the number of ASVs assigned to each phylum.

## 
##     Actinobacteria      Bacteroidetes        Chloroflexi 
##                 96               1257                 39 
##      Cyanobacteria    Deferribacteres      Elusimicrobia 
##                 74                  1                 16 
## Epsilonbacteraeota      Euryarchaeota      Fibrobacteres 
##                  2                 44                 39 
##         Firmicutes       Fusobacteria   Gemmatimonadetes 
##               3095                  4                  1 
## Kiritimatiellaeota      Lentisphaerae    Patescibacteria 
##                180                 31                 14 
##     Planctomycetes     Proteobacteria       Spirochaetes 
##                 15                222                138 
##      Synergistetes        Tenericutes    Verrucomicrobia 
##                  6                188                 35 
##               <NA> 
##                 94
Next we will count what samples have the ASVs that aren’t assigned to a phylum.

There are 94 ASVs that weren’t able to be assigned to a phylum. These unassigned taxa are found in all sample types with most of the unassigned ASVs in solid samples. NOTE that the sum column is reads not the number of ASVs! We next made a fasta file from the phyloseq object with these unknown taxa so that we can blast it later.

Getting back to our orginal phyloseq object: the 94 AVSs that weren’t assigned to a phyla were removed for analysis. This leaves 5,497 ASVs.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5497 taxa and 68 samples ]
## sample_data() Sample Data:       [ 68 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5497 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5497 tips and 5495 internal nodes ]

Next we will compute the total and average prevalences of the ASVs in each phylum. We are defining prevalence as the number of samples in which a taxon appears at least once.

Prevelance of Phyla
Phylum 1 2
Actinobacteria 19.78125 1899
Bacteroidetes 22.49483 28276
Chloroflexi 28.66667 1118
Cyanobacteria 14.45946 1070
Deferribacteres 1.00000 1
Elusimicrobia 23.43750 375
Epsilonbacteraeota 19.00000 38
Euryarchaeota 31.36364 1380
Fibrobacteres 31.00000 1209
Firmicutes 22.81874 70624
Fusobacteria 9.50000 38
Gemmatimonadetes 1.00000 1
Kiritimatiellaeota 19.97778 3596
Lentisphaerae 15.12903 469
Patescibacteria 26.00000 364
Planctomycetes 20.06667 301
Proteobacteria 15.32432 3402
Spirochaetes 21.03623 2903
Synergistetes 19.50000 117
Tenericutes 19.53191 3672
Verrucomicrobia 18.42857 645

Here we see that Deferribacteres and Gemmatimonadetes ASVs only has one feature so we’ll just looking into this real quick.

## [1] "Stomach Tube"
## OTU Table:          [1 taxa and 1 samples]
##                      taxa are rows
##          282
## ASV_5560   3
## [1] "Feces"
## OTU Table:          [1 taxa and 1 samples]
##                      taxa are rows
##          370
## ASV_5602   2

The phylum Deferribacteres are only in Fecal samples (2 reads) and and Gemmatimonadetes are only in Stomach Tube samples (3 reads). This suggest these groups might be important for comparing sample types, thus we will leave reads assigned to these phyla in the dataset despite their low prevelance.

Lastly, we’ll check to see if chloroplasts and Mitochondria are in the data set and remove them.

After removing chloroplasts and mitochondria there is 5,485 ASVs left.

Looking at metrics after filtering

As we have seen previously, there are 5485 ASVs in the dataset. This is composed of 21 phyla, 78 Orders, 116 Families and 293 Genera.

5393 ASVs didn’t have species assigned. Only 1.68% of taxa had species assigned. For genera, 1796 ASVs didn’t have a genera assigned. Only 67.3% of taxa had genera assigned.

Unassigned Species
Phylum #ASVs with no species assignment Total ASVs Percent Unassigned
Actinobacteria 90 96 93.75000
Bacteroidetes 1244 1257 98.96579
Chloroflexi 39 39 100.00000
Cyanobacteria 65 65 100.00000
Deferribacteres 1 1 100.00000
Elusimicrobia 16 16 100.00000
Epsilonbacteraeota 2 2 100.00000
Euryarchaeota 44 44 100.00000
Fibrobacteres 34 39 87.17949
Firmicutes 3046 3095 98.41680
Fusobacteria 1 4 25.00000
Gemmatimonadetes 1 1 100.00000
Kiritimatiellaeota 180 180 100.00000
Lentisphaerae 31 31 100.00000
Patescibacteria 14 14 100.00000
Planctomycetes 15 15 100.00000
Proteobacteria 207 219 94.52055
Spirochaetes 135 138 97.82609
Synergistetes 6 6 100.00000
Tenericutes 188 188 100.00000
Verrucomicrobia 34 35 97.14286

This table gives the frequencing and percent of ASVs not assigned to species and their phyla. This really speaks to the limitations of the methods used here to be able to give species level assigments.

This table gives the frequencing and percent of ASVs not assigned to genus and their phyla.

There are 86 singletons (20), doubletons (37) or tripletons (29). This looks pretty good and indicates that filtering was not excessive nor was a large enough part of the data to be suspicious about. We will need these for diversity metrics.

For the last part of our cleaning process we will graph out the prevalance of ASVs assigned to each phylum.

Rechecking read stats

Before moving on we will look again at the read stats to check that we still don’t have reads that are too long in the dataset.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5485 taxa and 68 samples ]
## sample_data() Sample Data:       [ 68 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5485 taxa by 7 taxonomic ranks ]
## 
##  229  230  232  246  252  253  254  255  263  269  270  271  281  287  294 
##    3    7    1    1  851 4449  129    6    2    7   23    2    1    1    1 
##  342 
##    1

Looks like we now only have one sample that is greater than 300bp let’s see what it is.

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##                                                                                                                                                                                                                                                                                                                                                        Kingdom  
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Archaea"
##                                                                                                                                                                                                                                                                                                                                                        Phylum         
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Euryarchaeota"
##                                                                                                                                                                                                                                                                                                                                                        Class            
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteria"
##                                                                                                                                                                                                                                                                                                                                                        Order               
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteriales"
##                                                                                                                                                                                                                                                                                                                                                        Family               
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobacteriaceae"
##                                                                                                                                                                                                                                                                                                                                                        Genus               
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG "Methanobrevibacter"
##                                                                                                                                                                                                                                                                                                                                                        Species
## CACCGGCAGCTCTAGTGGTAGCTGTTTTTATTGGGCCTAAAGCGTTCGTAGCCGGTTTAATAAGTCTCTGGTGAAATCCTATAGCTTAACTGTGGGAATTGCTGGAGATACTATTAGACTTGAGATCGGGAGAGGTCAGAGGTACTCCTGGGGTAGGGGTGAAATCCTGTAATCCTAGGAGGACCACCTGTGGCGAAGGCGTCTGACTAGAACGAATCTGACGGTGAGGAACGAAAGCTAGGGGCGGTGAAATGCGTAGATATGCCACAGAACGCCGTTGGCGGAGGCGGCTCGCCAGGCCTGCATTGACGCTCGGGCACGAAAGCGTGGGGATCGAACAGG NA

As this large sequence is a Methanobrevibacter and this is a common rumen bacteria its expected to be here and will be left in the data set.

Abundance of Phyla

As the first part of the exploratory analysis we will look the general relative abundances of phyla across sample types.

Statistiscs for Abundance of Phyla
Sample_Type Phylum mean sd sem
94 Solid Firmicutes 67.171193 1.89788 0.547872
115 Stomach Tube Firmicutes 64.680196 7.64829 2.207872
31 Grab Sample Firmicutes 64.309812 6.22378 1.796650
10 Feces Firmicutes 61.237127 3.58700 1.035479
73 Liquid Unstrained Firmicutes 55.214891 6.56683 2.321726
52 Liquid Strained Firmicutes 43.521396 3.83594 1.107340
44 Liquid Strained Bacteroidetes 33.325984 3.48697 1.006602
2 Feces Bacteroidetes 32.089477 3.22568 0.931172
65 Liquid Unstrained Bacteroidetes 26.470699 2.42579 0.857646
107 Stomach Tube Bacteroidetes 20.863182 4.86305 1.403841
86 Solid Bacteroidetes 20.221741 2.76979 0.799571
23 Grab Sample Bacteroidetes 19.959058 2.22827 0.643245
55 Liquid Strained Kiritimatiellaeota 6.959357 1.43120 0.413151
39 Grab Sample Spirochaetes 4.123484 7.67724 2.216229
76 Liquid Unstrained Kiritimatiellaeota 3.954869 2.05528 0.726650
59 Liquid Strained Proteobacteria 3.891003 1.39286 0.402083
113 Stomach Tube Euryarchaeota 3.329381 1.35194 0.390270
92 Solid Euryarchaeota 3.167559 1.78381 0.514941
80 Liquid Unstrained Proteobacteria 3.012016 1.47040 0.519864
29 Grab Sample Euryarchaeota 2.518253 0.87016 0.251193
71 Liquid Unstrained Euryarchaeota 2.360323 1.42703 0.504532
60 Liquid Strained Spirochaetes 2.259901 0.81533 0.235364
50 Liquid Strained Euryarchaeota 2.202896 1.40978 0.406970
30 Grab Sample Fibrobacteres 2.182511 0.52162 0.150579
62 Liquid Strained Tenericutes 2.007239 0.41986 0.121202
81 Liquid Unstrained Spirochaetes 1.937928 0.95423 0.337371
83 Liquid Unstrained Tenericutes 1.883149 0.54376 0.192247
118 Stomach Tube Kiritimatiellaeota 1.850052 1.30901 0.377879
122 Stomach Tube Proteobacteria 1.813390 0.85311 0.246273
51 Liquid Strained Fibrobacteres 1.790122 0.68267 0.197069
106 Stomach Tube Actinobacteria 1.593072 0.44466 0.128362
38 Grab Sample Proteobacteria 1.577367 0.39181 0.113107
125 Stomach Tube Tenericutes 1.562888 0.47927 0.138353
101 Solid Proteobacteria 1.514819 0.53489 0.154410
93 Solid Fibrobacteres 1.440196 0.59696 0.172328
21 Feces Verrucomicrobia 1.330008 0.53676 0.154950
41 Grab Sample Tenericutes 1.327798 0.18652 0.053844
85 Solid Actinobacteria 1.218782 0.30407 0.087779
102 Solid Spirochaetes 1.117817 0.37786 0.109078
123 Stomach Tube Spirochaetes 1.110958 0.63550 0.183454
22 Grab Sample Actinobacteria 1.097541 0.22664 0.065427
104 Solid Tenericutes 1.083357 0.17849 0.051527
17 Feces Proteobacteria 1.076418 0.31832 0.091890
20 Feces Tenericutes 0.974926 0.22835 0.065918
34 Grab Sample Kiritimatiellaeota 0.949299 0.11497 0.033190
72 Liquid Unstrained Fibrobacteres 0.924121 0.57314 0.202635
64 Liquid Unstrained Actinobacteria 0.924064 0.33227 0.117476
46 Liquid Strained Cyanobacteria 0.886615 0.36020 0.103981
13 Feces Kiritimatiellaeota 0.842224 0.34891 0.100721
97 Solid Kiritimatiellaeota 0.811684 0.13214 0.038147
99 Solid Patescibacteria 0.696159 0.18816 0.054316
43 Liquid Strained Actinobacteria 0.687316 0.30537 0.088154
87 Solid Chloroflexi 0.680062 0.19086 0.055096
56 Liquid Strained Lentisphaerae 0.671255 0.19280 0.055656
108 Stomach Tube Chloroflexi 0.663903 0.15329 0.044252
8 Feces Euryarchaeota 0.636827 0.34124 0.098507
67 Liquid Unstrained Cyanobacteria 0.622941 0.41690 0.147396
77 Liquid Unstrained Lentisphaerae 0.620633 0.41150 0.145487
126 Stomach Tube Verrucomicrobia 0.609821 0.21143 0.061034
24 Grab Sample Chloroflexi 0.584714 0.13518 0.039024
66 Liquid Unstrained Chloroflexi 0.544889 0.08668 0.030645
84 Liquid Unstrained Verrucomicrobia 0.540529 0.14486 0.051215
36 Grab Sample Patescibacteria 0.531587 0.17283 0.049892
78 Liquid Unstrained Patescibacteria 0.525094 0.16369 0.057872
57 Liquid Strained Patescibacteria 0.480896 0.12887 0.037201
4 Feces Cyanobacteria 0.449117 0.13271 0.038309
119 Stomach Tube Lentisphaerae 0.442976 0.32682 0.094345
45 Liquid Strained Chloroflexi 0.421857 0.11367 0.032813
1 Feces Actinobacteria 0.407788 0.11409 0.032934
63 Liquid Strained Verrucomicrobia 0.392914 0.11300 0.032619
120 Stomach Tube Patescibacteria 0.365494 0.15142 0.043712
48 Liquid Strained Elusimicrobia 0.363036 0.20188 0.058278
114 Stomach Tube Fibrobacteres 0.354001 0.23941 0.069110
105 Solid Verrucomicrobia 0.339158 0.06796 0.019618
42 Grab Sample Verrucomicrobia 0.330473 0.10189 0.029413
18 Feces Spirochaetes 0.328016 0.21602 0.062360
69 Liquid Unstrained Elusimicrobia 0.317035 0.18254 0.064539
109 Stomach Tube Cyanobacteria 0.274073 0.25401 0.073326
14 Feces Lentisphaerae 0.237553 0.18456 0.053277
16 Feces Planctomycetes 0.195166 0.07189 0.020753
111 Stomach Tube Elusimicrobia 0.156546 0.13165 0.038005
90 Solid Elusimicrobia 0.151592 0.08210 0.023700
25 Grab Sample Cyanobacteria 0.139923 0.06311 0.018219
116 Stomach Tube Fusobacteria 0.130143 0.11210 0.032361
121 Stomach Tube Planctomycetes 0.126690 0.04305 0.012427
103 Solid Synergistetes 0.121142 0.03615 0.010437
27 Grab Sample Elusimicrobia 0.111197 0.04869 0.014056
100 Solid Planctomycetes 0.102944 0.01891 0.005458
6 Feces Elusimicrobia 0.097389 0.05545 0.016006
37 Grab Sample Planctomycetes 0.096631 0.04228 0.012205
88 Solid Cyanobacteria 0.095623 0.06059 0.017491
79 Liquid Unstrained Planctomycetes 0.087836 0.03479 0.012301
35 Grab Sample Lentisphaerae 0.077359 0.04240 0.012241
40 Grab Sample Synergistetes 0.076985 0.04797 0.013848
58 Liquid Strained Planctomycetes 0.064471 0.03202 0.009243
98 Solid Lentisphaerae 0.056500 0.02380 0.006872
124 Stomach Tube Synergistetes 0.052609 0.04184 0.012079
82 Liquid Unstrained Synergistetes 0.048419 0.01954 0.006910
61 Liquid Strained Synergistetes 0.045930 0.02969 0.008572
7 Feces Epsilonbacteraeota 0.036546 0.02753 0.007948
3 Feces Chloroflexi 0.033252 0.01365 0.003940
49 Liquid Strained Epsilonbacteraeota 0.020465 0.02449 0.007068
9 Feces Fibrobacteres 0.017672 0.01711 0.004938
112 Stomach Tube Epsilonbacteraeota 0.016921 0.02402 0.006934
53 Liquid Strained Fusobacteria 0.007350 0.01514 0.004369
91 Solid Epsilonbacteraeota 0.006537 0.00899 0.002595
70 Liquid Unstrained Epsilonbacteraeota 0.005759 0.00860 0.003042
15 Feces Patescibacteria 0.005358 0.00988 0.002851
74 Liquid Unstrained Fusobacteria 0.004807 0.01090 0.003854
117 Stomach Tube Gemmatimonadetes 0.003704 0.01283 0.003704
95 Solid Fusobacteria 0.003135 0.00469 0.001353
32 Grab Sample Fusobacteria 0.003029 0.00707 0.002042
28 Grab Sample Epsilonbacteraeota 0.002979 0.00739 0.002133
11 Feces Fusobacteria 0.002610 0.00473 0.001365
5 Feces Deferribacteres 0.001839 0.00637 0.001839
19 Feces Synergistetes 0.000688 0.00238 0.000688
12 Feces Gemmatimonadetes 0.000000 0.00000 0.000000
26 Grab Sample Deferribacteres 0.000000 0.00000 0.000000
33 Grab Sample Gemmatimonadetes 0.000000 0.00000 0.000000
47 Liquid Strained Deferribacteres 0.000000 0.00000 0.000000
54 Liquid Strained Gemmatimonadetes 0.000000 0.00000 0.000000
68 Liquid Unstrained Deferribacteres 0.000000 0.00000 0.000000
75 Liquid Unstrained Gemmatimonadetes 0.000000 0.00000 0.000000
89 Solid Deferribacteres 0.000000 0.00000 0.000000
96 Solid Gemmatimonadetes 0.000000 0.00000 0.000000
110 Stomach Tube Deferribacteres 0.000000 0.00000 0.000000

We will look at relative abundance of Phyla in certain sample types. First, grab samples.

Next, we examine the relative abundance of Phyla in only fecal samples.

These are the phyla found in all samples sorted by decending order of mean relative abundance.

We will have a look to see if any phyla only present in only feces or only in stomach tube samples.

Deferribacteres Was only found in fecal samples and Gemmatimonadetes was only found in stomach tube samples.

This confirms what we say earlier and we didn’t identify any other phyla that are only present in these sample types.

Next we will graph out some of the different phyla based on their abundance ranges.

This is a graph of the major phyla, defined as those present at an abundance greater than 3% relative abundance, in rumen samples. Next we will graph phyla less than 3% relative abundance.

This is a graph of the “minor” phyla, defined as present at an abundance below 3%, in rumen samples. I also made an interactive version of this graph to put a link for in the manuscript.

You can access the interactive figure here.Below is Figure 1 A & B.

## Saving 180 x 152 mm image

We will do the create the same graphs at the family level as well.

Abundance of families

This is a table of the relative abundances of families in all sample types.

Statistiscs for Abundance of fam
Sample_Type Family mean sd sem
96 Feces Ruminococcaceae 40.662043 2.17531 0.627959
171 Grab Sample Lachnospiraceae 25.909379 2.13026 0.614953
516 Solid Lachnospiraceae 24.978741 2.41347 0.696708
631 Stomach Tube Lachnospiraceae 23.893818 3.88265 1.120824
320 Liquid Strained Prevotellaceae 23.776220 3.98548 1.150509
556 Solid Ruminococcaceae 19.590277 0.60315 0.174115
487 Solid Christensenellaceae 19.580047 1.68893 0.487552
602 Stomach Tube Christensenellaceae 18.574572 1.73189 0.499955
441 Liquid Unstrained Ruminococcaceae 18.461506 1.59136 0.562629
142 Grab Sample Christensenellaceae 18.085232 2.72055 0.785356
671 Stomach Tube Ruminococcaceae 17.918312 1.45935 0.421278
401 Liquid Unstrained Lachnospiraceae 17.835313 2.41513 0.853876
211 Grab Sample Ruminococcaceae 17.481760 2.51743 0.726720
372 Liquid Unstrained Christensenellaceae 16.812558 2.68812 0.950394
435 Liquid Unstrained Prevotellaceae 16.146729 2.34486 0.829034
95 Feces Rikenellaceae 15.692367 2.04158 0.589352
326 Liquid Strained Ruminococcaceae 15.458665 1.76966 0.510857
286 Liquid Strained Lachnospiraceae 15.089913 1.75205 0.505772
257 Liquid Strained Christensenellaceae 12.142322 1.44194 0.416253
665 Stomach Tube Prevotellaceae 10.533860 3.46172 0.999311
550 Solid Prevotellaceae 9.172494 1.41162 0.407499
205 Grab Sample Prevotellaceae 8.656660 1.49577 0.431791
555 Solid Rikenellaceae 7.756655 1.17414 0.338944
56 Feces Lachnospiraceae 7.718256 1.85419 0.535258
27 Feces Christensenellaceae 7.483265 1.06576 0.307660
210 Grab Sample Rikenellaceae 7.475779 1.14093 0.329358
11 Feces Bacteroidaceae 7.403751 0.87114 0.251478
670 Stomach Tube Rikenellaceae 7.375575 1.78391 0.514971
440 Liquid Unstrained Rikenellaceae 6.348289 1.01506 0.358878
90 Feces Prevotellaceae 6.258670 1.21983 0.352134
325 Liquid Strained Rikenellaceae 5.326237 1.30835 0.377688
217 Grab Sample Spirochaetaceae 4.279276 8.11607 2.342907
277 Liquid Strained F082 4.166934 0.94223 0.271998
638 Stomach Tube Methanobacteriaceae 3.290438 1.39475 0.402629
523 Solid Methanobacteriaceae 3.006646 1.84641 0.533014
86 Feces Peptostreptococcaceae 2.894522 0.89910 0.259548
392 Liquid Unstrained F082 2.882237 0.41067 0.145192
624 Stomach Tube Family_XIII 2.719298 0.57073 0.164756
509 Solid Family_XIII 2.651126 0.58246 0.168141
49 Feces Family_XIII 2.577243 0.65975 0.190455
178 Grab Sample Methanobacteriaceae 2.464815 0.92852 0.268041
164 Grab Sample Family_XIII 2.446497 0.58196 0.167996
332 Liquid Strained Spirochaetaceae 2.408240 0.91161 0.263159
408 Liquid Unstrained Methanobacteriaceae 2.287936 1.46200 0.516895
165 Grab Sample Fibrobacteraceae 2.286694 0.54644 0.157744
293 Liquid Strained Methanobacteriaceae 2.243293 1.52734 0.440906
342 Liquid Strained Veillonellaceae 2.113366 0.56986 0.164503
394 Liquid Unstrained Family_XIII 2.030927 0.50719 0.179319
447 Liquid Unstrained Spirochaetaceae 2.023389 1.06782 0.377533
280 Liquid Strained Fibrobacteraceae 2.017938 0.79045 0.228183
622 Stomach Tube F082 1.883605 0.94966 0.274142
250 Liquid Strained Burkholderiaceae 1.613253 1.14707 0.331132
162 Grab Sample F082 1.573685 0.31899 0.092086
457 Liquid Unstrained Veillonellaceae 1.558952 0.80191 0.283518
336 Liquid Strained Succinivibrionaceae 1.543685 0.60789 0.175483
620 Stomach Tube Erysipelotrichaceae 1.537342 0.29198 0.084288
510 Solid Fibrobacteraceae 1.505930 0.62518 0.180473
507 Solid F082 1.479020 0.40472 0.116833
5 Feces Akkermansiaceae 1.399232 0.56693 0.163658
243 Liquid Strained Bacteroidales_RF16_group 1.369223 0.39137 0.112979
308 Liquid Strained p-251-o5 1.337976 0.62608 0.180735
279 Liquid Strained Family_XIII 1.318429 0.37085 0.107056
365 Liquid Unstrained Burkholderiaceae 1.116637 0.97066 0.343179
562 Solid Spirochaetaceae 1.100219 0.34829 0.100541
677 Stomach Tube Spirochaetaceae 1.099645 0.62883 0.181527
680 Stomach Tube Streptococcaceae 1.095366 0.92407 0.266756
275 Liquid Strained Erysipelotrichaceae 1.070523 0.37997 0.109687
390 Liquid Unstrained Erysipelotrichaceae 1.065354 0.19851 0.070183
451 Liquid Unstrained Succinivibrionaceae 1.052210 0.67959 0.240271
237 Liquid Strained Anaeroplasmataceae 1.026677 0.33767 0.097476
395 Liquid Unstrained Fibrobacteraceae 1.017878 0.65786 0.232590
583 Stomach Tube Atopobiaceae 1.006651 0.40293 0.116316
463 Solid Acidaminococcaceae 0.980055 0.25973 0.074976
160 Grab Sample Erysipelotrichaceae 0.972573 0.17214 0.049692
352 Liquid Unstrained Anaeroplasmataceae 0.951233 0.35690 0.126184
358 Liquid Unstrained Bacteroidales_RF16_group 0.869041 0.28465 0.100640
423 Liquid Unstrained p-251-o5 0.851984 0.25395 0.089786
505 Solid Erysipelotrichaceae 0.840776 0.18666 0.053883
45 Feces Erysipelotrichaceae 0.825341 0.17601 0.050811
227 Grab Sample Veillonellaceae 0.748046 0.18592 0.053671
79 Feces p-2534-18B5_gut_group 0.745844 0.49756 0.143633
466 Solid Anaerolineaceae 0.710695 0.19884 0.057401
581 Stomach Tube Anaerolineaceae 0.699699 0.15876 0.045830
13 Feces Bacteroidales_RF16_group 0.681372 0.16245 0.046895
348 Liquid Unstrained Acidaminococcaceae 0.679111 0.18720 0.066184
687 Stomach Tube Veillonellaceae 0.677002 0.41223 0.119001
341 Liquid Strained vadinBE97 0.668188 0.20766 0.059946
357 Liquid Unstrained Bacteroidales_BS11_gut_group 0.647920 0.23197 0.082014
353 Liquid Unstrained Atopobiaceae 0.644468 0.30347 0.107292
242 Liquid Strained Bacteroidales_BS11_gut_group 0.636461 0.16085 0.046432
127 Grab Sample Bacteroidales_BS11_gut_group 0.633199 0.16352 0.047204
472 Solid Bacteroidales_BS11_gut_group 0.626981 0.16838 0.048607
456 Liquid Unstrained vadinBE97 0.619314 0.42255 0.149393
121 Grab Sample Anaerolineaceae 0.612631 0.14162 0.040881
63 Feces Methanobacteriaceae 0.596446 0.37468 0.108160
351 Liquid Unstrained Anaerolineaceae 0.590020 0.08645 0.030563
118 Grab Sample Acidaminococcaceae 0.577466 0.10489 0.030280
500 Solid Eggerthellaceae 0.566750 0.12475 0.036012
36 Feces Desulfovibrionaceae 0.560810 0.27123 0.078297
496 Solid Desulfovibrionaceae 0.559735 0.21469 0.061977
123 Grab Sample Atopobiaceae 0.556082 0.11200 0.032332
582 Stomach Tube Anaeroplasmataceae 0.550660 0.27169 0.078429
193 Grab Sample p-251-o5 0.534799 0.26332 0.076013
468 Solid Atopobiaceae 0.533660 0.15493 0.044724
151 Grab Sample Desulfovibrionaceae 0.530917 0.17663 0.050988
238 Liquid Strained Atopobiaceae 0.524360 0.29423 0.084937
611 Stomach Tube Desulfovibrionaceae 0.523125 0.17801 0.051387
578 Stomach Tube Acidaminococcaceae 0.520036 0.17769 0.051296
85 Feces Peptococcaceae 0.510863 0.10803 0.031186
530 Solid Muribaculaceae 0.501963 0.06935 0.020019
233 Liquid Strained Acidaminococcaceae 0.482755 0.14870 0.042927
615 Stomach Tube Eggerthellaceae 0.478785 0.15600 0.045032
155 Grab Sample Eggerthellaceae 0.475405 0.13575 0.039188
236 Liquid Strained Anaerolineaceae 0.473437 0.12683 0.036612
185 Grab Sample Muribaculaceae 0.463656 0.09160 0.026444
587 Stomach Tube Bacteroidales_BS11_gut_group 0.447419 0.23030 0.066483
686 Stomach Tube vadinBE97 0.435754 0.34089 0.098407
588 Stomach Tube Bacteroidales_RF16_group 0.420013 0.26444 0.076336
381 Liquid Unstrained Desulfovibrionaceae 0.392658 0.11058 0.039095
221 Grab Sample Succinivibrionaceae 0.380597 0.18977 0.054781
625 Stomach Tube Fibrobacteraceae 0.377099 0.25939 0.074878
645 Stomach Tube Muribaculaceae 0.369579 0.17473 0.050440
572 Solid Veillonellaceae 0.368549 0.10245 0.029575
259 Liquid Strained Clostridiales_vadinBB60_group 0.356928 0.09081 0.026215
102 Feces Spirochaetaceae 0.347187 0.22783 0.065768
47 Feces F082 0.341935 0.12590 0.036343
681 Stomach Tube Succinivibrionaceae 0.336053 0.27571 0.079590
595 Stomach Tube Burkholderiaceae 0.331625 0.27181 0.078465
3 Feces Acidaminococcaceae 0.319192 0.06945 0.020049
122 Grab Sample Anaeroplasmataceae 0.307062 0.11445 0.033038
80 Feces Paludibacteraceae 0.303656 0.13622 0.039325
266 Liquid Strained Desulfovibrionaceae 0.299891 0.08871 0.025609
525 Solid Methanomethylophilaceae 0.296907 0.08416 0.024296
653 Stomach Tube p-251-o5 0.296192 0.18872 0.054478
70 Feces Muribaculaceae 0.291696 0.10340 0.029848
538 Solid p-251-o5 0.288969 0.09724 0.028071
415 Liquid Unstrained Muribaculaceae 0.280209 0.11363 0.040174
374 Liquid Unstrained Clostridiales_vadinBB60_group 0.258308 0.14999 0.053031
385 Liquid Unstrained Eggerthellaceae 0.249293 0.09906 0.035025
271 Liquid Strained Elusimicrobiaceae 0.247167 0.10371 0.029938
29 Feces Clostridiales_vadinBB60_group 0.245353 0.15311 0.044200
410 Liquid Unstrained Methanomethylophilaceae 0.243601 0.08607 0.030432
480 Solid Burkholderiaceae 0.239162 0.24901 0.071882
128 Grab Sample Bacteroidales_RF16_group 0.228827 0.07427 0.021439
566 Solid Succinivibrionaceae 0.225922 0.16580 0.047861
335 Liquid Strained Streptococcaceae 0.215900 0.10879 0.031406
135 Grab Sample Burkholderiaceae 0.209240 0.10020 0.028926
295 Liquid Strained Methanomethylophilaceae 0.208475 0.09661 0.027889
87 Feces Pirellulaceae 0.206561 0.07625 0.022010
640 Stomach Tube Methanomethylophilaceae 0.202565 0.07348 0.021210
113 Feces Victivallaceae 0.198879 0.15588 0.044999
149 Grab Sample Defluviitaleaceae 0.196038 0.08053 0.023248
40 Feces Eggerthellaceae 0.189249 0.08373 0.024170
300 Liquid Strained Muribaculaceae 0.181475 0.09106 0.026286
450 Liquid Unstrained Streptococcaceae 0.179921 0.08149 0.028811
270 Liquid Strained Eggerthellaceae 0.176277 0.08897 0.025683
200 Grab Sample Peptococcaceae 0.175800 0.10497 0.030303
386 Liquid Unstrained Elusimicrobiaceae 0.175441 0.11458 0.040510
387 Liquid Unstrained Endomicrobiaceae 0.173038 0.12007 0.042452
180 Grab Sample Methanomethylophilaceae 0.170696 0.06650 0.019196
545 Solid Peptococcaceae 0.167197 0.05052 0.014583
609 Stomach Tube Defluviitaleaceae 0.166117 0.06242 0.018019
467 Solid Anaeroplasmataceae 0.162214 0.05784 0.016697
473 Solid Bacteroidales_RF16_group 0.161196 0.07571 0.021855
272 Liquid Strained Endomicrobiaceae 0.159378 0.14788 0.042690
494 Solid Defluviitaleaceae 0.148982 0.04836 0.013962
604 Stomach Tube Clostridiales_vadinBB60_group 0.143844 0.12588 0.036339
660 Stomach Tube Peptococcaceae 0.143545 0.07142 0.020618
28 Feces Clostridiaceae_1 0.137297 0.06146 0.017742
617 Stomach Tube Endomicrobiaceae 0.134121 0.12862 0.037130
662 Stomach Tube Pirellulaceae 0.133296 0.04368 0.012609
502 Solid Endomicrobiaceae 0.132840 0.07372 0.021281
565 Solid Streptococcaceae 0.130788 0.16399 0.047341
19 Feces Bifidobacteriaceae 0.128085 0.06899 0.019915
567 Solid Synergistaceae 0.126694 0.03795 0.010956
177 Grab Sample Marinilabiliaceae 0.122366 0.04732 0.013661
220 Grab Sample Streptococcaceae 0.113880 0.08490 0.024509
379 Liquid Unstrained Defluviitaleaceae 0.113587 0.04419 0.015625
475 Solid Bacteroidetes_BD2-2 0.110198 0.05620 0.016224
547 Solid Pirellulaceae 0.107592 0.01948 0.005622
130 Grab Sample Bacteroidetes_BD2-2 0.106388 0.04375 0.012630
627 Stomach Tube Fusobacteriaceae 0.105689 0.09255 0.026717
41 Feces Elusimicrobiaceae 0.102092 0.05904 0.017042
202 Grab Sample Pirellulaceae 0.101176 0.04403 0.012711
522 Solid Marinilabiliaceae 0.097609 0.06302 0.018191
8 Feces Atopobiaceae 0.095450 0.04035 0.011648
432 Liquid Unstrained Pirellulaceae 0.094921 0.03686 0.013033
20 Feces Burkholderiaceae 0.089456 0.04516 0.013035
430 Liquid Unstrained Peptococcaceae 0.088746 0.07321 0.025885
157 Grab Sample Endomicrobiaceae 0.088366 0.05187 0.014973
343 Liquid Strained Victivallaceae 0.086966 0.04126 0.011909
222 Grab Sample Synergistaceae 0.080729 0.05044 0.014561
407 Liquid Unstrained Marinilabiliaceae 0.079882 0.04409 0.015587
428 Liquid Unstrained Pedosphaeraceae 0.078697 0.03959 0.013997
637 Stomach Tube Marinilabiliaceae 0.078628 0.07002 0.020213
16 Feces Barnesiellaceae 0.076851 0.02568 0.007414
544 Solid PeH15 0.074235 0.02913 0.008409
313 Liquid Strained Pedosphaeraceae 0.073596 0.06269 0.018096
34 Feces Defluviitaleaceae 0.073182 0.03254 0.009394
64 Feces Methanocorpusculaceae 0.072398 0.05968 0.017228
317 Liquid Strained Pirellulaceae 0.072235 0.03548 0.010242
606 Stomach Tube Coriobacteriales_Incertae_Sedis 0.071326 0.05090 0.014695
586 Stomach Tube Bacteroidaceae 0.071087 0.11475 0.033127
226 Grab Sample vadinBE97 0.070891 0.04038 0.011656
287 Liquid Strained Lactobacillaceae 0.069775 0.06637 0.019159
161 Grab Sample Eubacteriaceae 0.068736 0.03572 0.010310
658 Stomach Tube Pedosphaeraceae 0.067406 0.06005 0.017336
61 Feces Marinifilaceae 0.066216 0.04162 0.012014
659 Stomach Tube PeH15 0.064715 0.03626 0.010466
458 Liquid Unstrained Victivallaceae 0.064524 0.05513 0.019492
199 Grab Sample PeH15 0.063409 0.04192 0.012101
621 Stomach Tube Eubacteriaceae 0.063345 0.03978 0.011483
78 Feces p-251-o5 0.062782 0.05180 0.014954
264 Liquid Strained Defluviitaleaceae 0.062671 0.03757 0.010845
657 Stomach Tube Pasteurellaceae 0.061972 0.06716 0.019389
311 Liquid Strained Paracaedibacteraceae 0.061309 0.03007 0.008679
53 Feces GZKB124 0.060164 0.11122 0.032107
623 Stomach Tube Family_XI 0.059822 0.06603 0.019060
321 Liquid Strained Pseudomonadaceae 0.059767 0.06805 0.019645
529 Solid Moraxellaceae 0.059274 0.16647 0.048055
506 Solid Eubacteriaceae 0.059031 0.03127 0.009028
88 Feces Planococcaceae 0.058235 0.07061 0.020384
402 Liquid Unstrained Lactobacillaceae 0.058117 0.03608 0.012757
146 Grab Sample Coriobacteriales_Incertae_Sedis 0.057232 0.02890 0.008343
491 Solid Coriobacteriales_Incertae_Sedis 0.056256 0.02149 0.006204
292 Liquid Strained Marinilabiliaceae 0.056163 0.04938 0.014256
682 Stomach Tube Synergistaceae 0.056113 0.04641 0.013396
632 Stomach Tube Lactobacillaceae 0.055846 0.04092 0.011811
315 Liquid Strained Peptococcaceae 0.055806 0.03613 0.010430
543 Solid Pedosphaeraceae 0.055375 0.03722 0.010745
571 Solid vadinBE97 0.053217 0.02680 0.007737
452 Liquid Unstrained Synergistaceae 0.052819 0.02235 0.007901
492 Solid Corynebacteriaceae 0.052490 0.10735 0.030990
111 Feces vadinBE97 0.052321 0.04605 0.013293
337 Liquid Strained Synergistaceae 0.051608 0.03343 0.009650
426 Liquid Unstrained Paracaedibacteraceae 0.051468 0.03729 0.013182
109 Feces Tannerellaceae 0.051042 0.03069 0.008859
391 Liquid Unstrained Eubacteriaceae 0.050990 0.03438 0.012154
356 Liquid Unstrained Bacteroidaceae 0.049972 0.03979 0.014067
14 Feces Bacteroidales_UCG-001 0.048206 0.02883 0.008322
258 Liquid Strained Clostridiaceae_1 0.047419 0.03865 0.011159
429 Liquid Unstrained PeH15 0.046158 0.02941 0.010398
416 Liquid Unstrained Mycoplasmataceae 0.045288 0.03608 0.012755
436 Liquid Unstrained Pseudomonadaceae 0.045214 0.03532 0.012487
474 Solid Bacteroidales_UCG-001 0.044178 0.02459 0.007097
661 Stomach Tube Peptostreptococcaceae 0.043530 0.01594 0.004601
152 Grab Sample Desulfuromonadaceae 0.042774 0.02832 0.008176
597 Stomach Tube Cardiobacteriaceae 0.042566 0.03387 0.009777
198 Grab Sample Pedosphaeraceae 0.042548 0.03695 0.010668
541 Solid Paracaedibacteraceae 0.040868 0.03335 0.009629
656 Stomach Tube Paracaedibacteraceae 0.040550 0.02568 0.007413
590 Stomach Tube Bacteroidetes_BD2-2 0.039367 0.02317 0.006689
105 Feces Streptococcaceae 0.039274 0.02798 0.008078
2 Feces Acetobacteraceae 0.039145 0.03724 0.010751
21 Feces Campylobacteraceae 0.038741 0.02917 0.008419
497 Solid Desulfuromonadaceae 0.038547 0.02360 0.006813
688 Stomach Tube Victivallaceae 0.038405 0.03573 0.010315
241 Liquid Strained Bacteroidaceae 0.037620 0.03860 0.011143
323 Liquid Strained Rhizobiaceae 0.037541 0.03476 0.010035
231 Liquid Strained 0319-6G20 0.037199 0.02142 0.006184
644 Stomach Tube Moraxellaceae 0.037051 0.04045 0.011677
129 Grab Sample Bacteroidales_UCG-001 0.036976 0.02393 0.006907
316 Liquid Strained Peptostreptococcaceae 0.036531 0.03227 0.009316
553 Solid Rhizobiaceae 0.035823 0.03217 0.009286
360 Liquid Unstrained Bacteroidetes_BD2-2 0.035561 0.01890 0.006682
126 Grab Sample Bacteroidaceae 0.035532 0.02987 0.008624
6 Feces Anaerolineaceae 0.035167 0.01434 0.004140
589 Stomach Tube Bacteroidales_UCG-001 0.034726 0.03563 0.010285
346 Liquid Unstrained 0319-6G20 0.034156 0.03848 0.013604
382 Liquid Unstrained Desulfuromonadaceae 0.033825 0.01931 0.006827
616 Stomach Tube Elusimicrobiaceae 0.033798 0.02366 0.006829
642 Stomach Tube Microbacteriaceae 0.032809 0.03284 0.009479
546 Solid Peptostreptococcaceae 0.032794 0.02061 0.005950
431 Liquid Unstrained Peptostreptococcaceae 0.032204 0.01756 0.006207
57 Feces Lactobacillaceae 0.031440 0.02677 0.007727
359 Liquid Unstrained Bacteroidales_UCG-001 0.031398 0.02176 0.007693
668 Stomach Tube Rhizobiaceae 0.030916 0.03065 0.008848
517 Solid Lactobacillaceae 0.030634 0.02465 0.007115
633 Stomach Tube Leptotrichiaceae 0.030396 0.05006 0.014450
245 Liquid Strained Bacteroidetes_BD2-2 0.030274 0.01563 0.004511
377 Liquid Unstrained Corynebacteriaceae 0.029443 0.03101 0.010962
446 Liquid Unstrained Sphingomonadaceae 0.029357 0.03590 0.012692
607 Stomach Tube Corynebacteriaceae 0.029047 0.02805 0.008098
143 Grab Sample Clostridiaceae_1 0.027773 0.02463 0.007111
471 Solid Bacteroidaceae 0.027522 0.02366 0.006831
201 Grab Sample Peptostreptococcaceae 0.027319 0.01781 0.005141
666 Stomach Tube Pseudomonadaceae 0.026882 0.03445 0.009944
244 Liquid Strained Bacteroidales_UCG-001 0.026616 0.02990 0.008630
156 Grab Sample Elusimicrobiaceae 0.026613 0.02532 0.007308
647 Stomach Tube Neisseriaceae 0.026201 0.03804 0.010980
176 Grab Sample Marinifilaceae 0.025995 0.02105 0.006077
172 Grab Sample Lactobacillaceae 0.025950 0.02155 0.006222
676 Stomach Tube Sphingomonadaceae 0.025676 0.02909 0.008398
388 Liquid Unstrained Enterobacteriaceae 0.025077 0.01960 0.006928
501 Solid Elusimicrobiaceae 0.024949 0.01781 0.005143
144 Grab Sample Clostridiales_vadinBB60_group 0.024787 0.02238 0.006461
373 Liquid Unstrained Clostridiaceae_1 0.024771 0.00887 0.003136
110 Feces Terasakiellaceae 0.024248 0.02840 0.008198
561 Solid Sphingomonadaceae 0.024161 0.02685 0.007751
331 Liquid Strained Sphingomonadaceae 0.024039 0.03042 0.008781
618 Stomach Tube Enterobacteriaceae 0.024030 0.02673 0.007718
437 Liquid Unstrained Puniceicoccaceae 0.023500 0.02735 0.009669
376 Liquid Unstrained Coriobacteriales_Incertae_Sedis 0.023124 0.01752 0.006196
520 Solid M2PB4-65_termite_group 0.022957 0.01940 0.005599
251 Liquid Strained Campylobacteraceae 0.022911 0.02738 0.007905
186 Grab Sample Mycoplasmataceae 0.022419 0.02510 0.007247
46 Feces Eubacteriaceae 0.022333 0.01495 0.004316
498 Solid Devosiaceae 0.022316 0.01422 0.004105
612 Stomach Tube Desulfuromonadaceae 0.022204 0.02251 0.006498
208 Grab Sample Rhizobiaceae 0.022144 0.02111 0.006094
314 Liquid Strained PeH15 0.022031 0.02670 0.007707
649 Stomach Tube Nocardiaceae 0.021847 0.01359 0.003923
488 Solid Clostridiaceae_1 0.021417 0.02079 0.006002
297 Liquid Strained Microbacteriaceae 0.021216 0.02142 0.006184
301 Liquid Strained Mycoplasmataceae 0.020624 0.02690 0.007766
196 Grab Sample Paracaedibacteraceae 0.020053 0.01779 0.005135
380 Liquid Unstrained Desulfobulbaceae 0.020019 0.02383 0.008426
655 Stomach Tube Paludibacteraceae 0.020009 0.01491 0.004304
490 Solid COB_P4-1_termite_group 0.019979 0.01485 0.004287
651 Stomach Tube Oligoflexaceae 0.019945 0.02065 0.005960
153 Grab Sample Devosiaceae 0.019573 0.01757 0.005071
262 Liquid Strained Corynebacteriaceae 0.019564 0.02327 0.006717
265 Liquid Strained Desulfobulbaceae 0.019531 0.01404 0.004054
521 Solid Marinifilaceae 0.019393 0.01509 0.004357
322 Liquid Strained Puniceicoccaceae 0.019346 0.02347 0.006774
527 Solid Microbacteriaceae 0.019278 0.01399 0.004039
414 Liquid Unstrained Moraxellaceae 0.019234 0.02319 0.008201
508 Solid Family_XI 0.019088 0.03173 0.009160
664 Stomach Tube Porphyromonadaceae 0.018788 0.02410 0.006958
50 Feces Fibrobacteraceae 0.018699 0.01805 0.005210
603 Stomach Tube Clostridiaceae_1 0.018597 0.01059 0.003057
596 Stomach Tube Campylobacteraceae 0.018162 0.02628 0.007585
216 Grab Sample Sphingomonadaceae 0.017641 0.01910 0.005513
584 Stomach Tube Bacillaceae 0.016902 0.02553 0.007370
406 Liquid Unstrained Marinifilaceae 0.016459 0.01805 0.006380
145 Grab Sample COB_P4-1_termite_group 0.016232 0.02194 0.006333
289 Liquid Strained Leuconostocaceae 0.016175 0.02517 0.007266
425 Liquid Unstrained Paludibacteraceae 0.016139 0.01815 0.006415
646 Stomach Tube Mycoplasmataceae 0.016099 0.01811 0.005228
568 Solid Syntrophomonadaceae 0.015737 0.00967 0.002791
610 Stomach Tube Desulfobulbaceae 0.015682 0.01561 0.004505
531 Solid Mycoplasmataceae 0.015630 0.02135 0.006162
158 Grab Sample Enterobacteriaceae 0.015240 0.02024 0.005844
663 Stomach Tube Planococcaceae 0.015003 0.01817 0.005244
147 Grab Sample Corynebacteriaceae 0.014852 0.01934 0.005584
672 Stomach Tube Saccharimonadaceae 0.014464 0.01235 0.003564
350 Liquid Unstrained Akkermansiaceae 0.014429 0.01506 0.005323
675 Stomach Tube Sphingobacteriaceae 0.014413 0.01673 0.004829
330 Liquid Strained Sphingobacteriaceae 0.014247 0.01833 0.005290
182 Grab Sample Microbacteriaceae 0.014190 0.01921 0.005545
613 Stomach Tube Devosiaceae 0.014048 0.01362 0.003931
540 Solid Paludibacteraceae 0.013924 0.01456 0.004203
412 Liquid Unstrained Microbacteriaceae 0.013779 0.01436 0.005077
445 Liquid Unstrained Sphingobacteriaceae 0.013391 0.02110 0.007460
273 Liquid Strained Enterobacteriaceae 0.013357 0.01312 0.003789
7 Feces Anaeroplasmataceae 0.013311 0.01168 0.003371
299 Liquid Strained Moraxellaceae 0.013064 0.01234 0.003563
175 Grab Sample M2PB4-65_termite_group 0.013056 0.01620 0.004676
163 Grab Sample Family_XI 0.012993 0.02246 0.006483
345 Liquid Strained Xanthomonadaceae 0.012979 0.01750 0.005051
278 Liquid Strained Family_XI 0.012832 0.01923 0.005552
291 Liquid Strained Marinifilaceae 0.012604 0.01120 0.003233
393 Liquid Unstrained Family_XI 0.012370 0.02313 0.008177
267 Liquid Strained Desulfuromonadaceae 0.012357 0.01448 0.004181
195 Grab Sample Paludibacteraceae 0.012100 0.01156 0.003336
438 Liquid Unstrained Rhizobiaceae 0.011973 0.01288 0.004553
465 Solid Akkermansiaceae 0.011909 0.00862 0.002487
503 Solid Enterobacteriaceae 0.011871 0.01258 0.003631
261 Liquid Strained Coriobacteriales_Incertae_Sedis 0.011861 0.01745 0.005038
504 Solid Enterococcaceae 0.011840 0.01326 0.003828
554 Solid Rhodobacteraceae 0.011757 0.03730 0.010766
375 Liquid Unstrained COB_P4-1_termite_group 0.011549 0.02044 0.007225
576 Stomach Tube 0319-6G20 0.011458 0.01144 0.003302
215 Grab Sample Sphingobacteriaceae 0.011142 0.01291 0.003728
690 Stomach Tube Xanthomonadaceae 0.011051 0.01697 0.004898
235 Liquid Strained Akkermansiaceae 0.010743 0.02096 0.006049
268 Liquid Strained Devosiaceae 0.010652 0.01544 0.004458
223 Grab Sample Syntrophomonadaceae 0.010589 0.01446 0.004173
634 Stomach Tube Leuconostocaceae 0.010566 0.01540 0.004446
206 Grab Sample Pseudomonadaceae 0.010421 0.01179 0.003403
667 Stomach Tube Puniceicoccaceae 0.010249 0.02161 0.006239
228 Grab Sample Victivallaceae 0.010203 0.01729 0.004990
605 Stomach Tube COB_P4-1_termite_group 0.010136 0.01922 0.005548
81 Feces Paracaedibacteraceae 0.010107 0.01009 0.002914
389 Liquid Unstrained Enterococcaceae 0.009852 0.01506 0.005324
139 Grab Sample Caulobacteraceae 0.009847 0.01328 0.003834
310 Liquid Strained Paludibacteraceae 0.009671 0.01383 0.003994
274 Liquid Strained Enterococcaceae 0.009554 0.01604 0.004630
552 Solid Puniceicoccaceae 0.009533 0.01480 0.004272
191 Grab Sample Oligoflexaceae 0.009434 0.01077 0.003110
306 Liquid Strained Oligoflexaceae 0.009407 0.01333 0.003848
212 Grab Sample Saccharimonadaceae 0.009296 0.01492 0.004306
324 Liquid Strained Rhodobacteraceae 0.009238 0.01977 0.005706
421 Liquid Unstrained Oligoflexaceae 0.009093 0.01400 0.004949
679 Stomach Tube Staphylococcaceae 0.008935 0.01114 0.003215
413 Liquid Unstrained Micrococcaceae 0.008915 0.00833 0.002947
460 Liquid Unstrained Xanthomonadaceae 0.008705 0.01069 0.003781
31 Feces Coriobacteriales_Incertae_Sedis 0.008646 0.01039 0.003000
92 Feces Puniceicoccaceae 0.008564 0.01106 0.003192
93 Feces Rhizobiaceae 0.008527 0.01238 0.003574
189 Grab Sample Nocardiaceae 0.008524 0.01372 0.003960
433 Liquid Unstrained Planococcaceae 0.008516 0.00977 0.003454
580 Stomach Tube Akkermansiaceae 0.008449 0.01822 0.005260
551 Solid Pseudomonadaceae 0.008411 0.01293 0.003731
439 Liquid Unstrained Rhodobacteraceae 0.008172 0.02311 0.008172
224 Grab Sample Tannerellaceae 0.008100 0.01354 0.003910
684 Stomach Tube Tannerellaceae 0.008024 0.01124 0.003245
442 Liquid Unstrained Saccharimonadaceae 0.007933 0.01167 0.004128
489 Solid Clostridiales_vadinBB60_group 0.007843 0.01064 0.003071
536 Solid Oligoflexaceae 0.007744 0.01022 0.002951
276 Liquid Strained Eubacteriaceae 0.007682 0.00900 0.002599
519 Solid Leuconostocaceae 0.007665 0.01402 0.004047
367 Liquid Unstrained Cardiobacteriaceae 0.007579 0.01131 0.004000
43 Feces Enterobacteriaceae 0.007410 0.01018 0.002940
636 Stomach Tube Marinifilaceae 0.007326 0.01163 0.003356
569 Solid Tannerellaceae 0.007273 0.00958 0.002766
643 Stomach Tube Micrococcaceae 0.007272 0.01320 0.003809
495 Solid Desulfobulbaceae 0.007171 0.00908 0.002621
364 Liquid Unstrained Bifidobacteriaceae 0.007158 0.00831 0.002938
106 Feces Succinivibrionaceae 0.007032 0.01058 0.003054
137 Grab Sample Cardiobacteriaceae 0.006916 0.01109 0.003202
579 Stomach Tube Aerococcaceae 0.006833 0.01062 0.003066
481 Solid Campylobacteraceae 0.006831 0.00938 0.002708
560 Solid Sphingobacteriaceae 0.006648 0.00984 0.002841
230 Grab Sample Xanthomonadaceae 0.006581 0.01284 0.003705
683 Stomach Tube Syntrophomonadaceae 0.006567 0.01018 0.002939
120 Grab Sample Akkermansiaceae 0.006546 0.01421 0.004101
366 Liquid Unstrained Campylobacteraceae 0.006356 0.00957 0.003384
73 Feces Nitrosomonadaceae 0.006290 0.01090 0.003147
383 Liquid Unstrained Devosiaceae 0.006279 0.00893 0.003156
673 Stomach Tube Sanguibacteraceae 0.006265 0.00960 0.002771
116 Grab Sample 0319-6G20 0.006238 0.00950 0.002741
454 Liquid Unstrained Tannerellaceae 0.006024 0.00927 0.003277
174 Grab Sample Leuconostocaceae 0.006018 0.00931 0.002688
150 Grab Sample Desulfobulbaceae 0.005998 0.00894 0.002582
282 Liquid Strained Fusobacteriaceae 0.005850 0.00960 0.002771
573 Solid Victivallaceae 0.005835 0.00943 0.002721
598 Stomach Tube Carnobacteriaceae 0.005834 0.01105 0.003190
564 Solid Staphylococcaceae 0.005711 0.00915 0.002642
312 Liquid Strained Pasteurellaceae 0.005474 0.00828 0.002390
405 Liquid Unstrained M2PB4-65_termite_group 0.005428 0.00770 0.002722
397 Liquid Unstrained Fusobacteriaceae 0.005345 0.01225 0.004331
558 Solid Sanguibacteraceae 0.005328 0.01039 0.003000
260 Liquid Strained COB_P4-1_termite_group 0.005313 0.01142 0.003296
362 Liquid Unstrained Beijerinckiaceae 0.005180 0.00800 0.002830
534 Solid Nocardiaceae 0.005171 0.00857 0.002473
294 Liquid Strained Methanocorpusculaceae 0.005139 0.00789 0.002277
417 Liquid Unstrained Neisseriaceae 0.004997 0.00765 0.002704
419 Liquid Unstrained Nocardiaceae 0.004994 0.00961 0.003397
339 Liquid Strained Tannerellaceae 0.004955 0.01071 0.003093
484 Solid Caulobacteraceae 0.004837 0.00800 0.002310
639 Stomach Tube Methanocorpusculaceae 0.004764 0.00910 0.002626
247 Liquid Strained Beijerinckiaceae 0.004646 0.00716 0.002066
12 Feces Bacteroidales_BS11_gut_group 0.004608 0.00728 0.002101
327 Liquid Strained Saccharimonadaceae 0.004565 0.00970 0.002799
453 Liquid Unstrained Syntrophomonadaceae 0.004527 0.00854 0.003018
619 Stomach Tube Enterococcaceae 0.004474 0.00879 0.002538
427 Liquid Unstrained Pasteurellaceae 0.004470 0.00619 0.002188
499 Solid Dysgonomonadaceae 0.004465 0.01358 0.003919
184 Grab Sample Moraxellaceae 0.004450 0.01144 0.003302
443 Liquid Unstrained Sanguibacteraceae 0.004430 0.00832 0.002943
65 Feces Methanomethylophilaceae 0.004428 0.00972 0.002806
197 Grab Sample Pasteurellaceae 0.004255 0.00774 0.002233
209 Grab Sample Rhodobacteraceae 0.004225 0.00780 0.002252
207 Grab Sample Puniceicoccaceae 0.004219 0.00768 0.002218
599 Stomach Tube Caulobacteraceae 0.004160 0.00807 0.002330
479 Solid Bifidobacteriaceae 0.004095 0.00831 0.002398
384 Liquid Unstrained Dysgonomonadaceae 0.004086 0.01156 0.004086
44 Feces Enterococcaceae 0.004080 0.00671 0.001937
592 Stomach Tube Beijerinckiaceae 0.003940 0.00739 0.002133
461 Solid 0319-6G20 0.003940 0.00608 0.001755
159 Grab Sample Enterococcaceae 0.003925 0.00723 0.002086
470 Solid Bacteriovoracaceae 0.003837 0.00739 0.002132
557 Solid Saccharimonadaceae 0.003777 0.00745 0.002152
449 Liquid Unstrained Staphylococcaceae 0.003708 0.00781 0.002761
252 Liquid Strained Cardiobacteriaceae 0.003585 0.00582 0.001680
404 Liquid Unstrained Leuconostocaceae 0.003440 0.00641 0.002266
302 Liquid Strained Neisseriaceae 0.003374 0.00613 0.001770
249 Liquid Strained Bifidobacteriaceae 0.003305 0.00617 0.001781
67 Feces Microbacteriaceae 0.003283 0.00643 0.001855
32 Feces Corynebacteriaceae 0.003280 0.00491 0.001417
512 Solid Fusobacteriaceae 0.003275 0.00490 0.001414
112 Feces Veillonellaceae 0.003185 0.00592 0.001708
338 Liquid Strained Syntrophomonadaceae 0.003165 0.00821 0.002370
239 Liquid Strained Bacillaceae 0.003149 0.00771 0.002227
136 Grab Sample Campylobacteraceae 0.003135 0.00778 0.002246
524 Solid Methanocorpusculaceae 0.003118 0.00475 0.001372
635 Stomach Tube M2PB4-65_termite_group 0.003070 0.00769 0.002219
234 Liquid Strained Aerococcaceae 0.003042 0.00810 0.002338
298 Liquid Strained Micrococcaceae 0.003002 0.00797 0.002300
218 Grab Sample Spirosomaceae 0.002993 0.00702 0.002026
409 Liquid Unstrained Methanocorpusculaceae 0.002976 0.00577 0.002039
213 Grab Sample Sanguibacteraceae 0.002882 0.00678 0.001956
340 Liquid Strained Terasakiellaceae 0.002859 0.00857 0.002473
125 Grab Sample Bacteriovoracaceae 0.002827 0.00666 0.001921
17 Feces Beijerinckiaceae 0.002809 0.00542 0.001564
594 Stomach Tube Bifidobacteriaceae 0.002795 0.00507 0.001463
318 Liquid Strained Planococcaceae 0.002769 0.00658 0.001901
334 Liquid Strained Staphylococcaceae 0.002763 0.00649 0.001874
52 Feces Fusobacteriaceae 0.002757 0.00500 0.001443
203 Grab Sample Planococcaceae 0.002692 0.00932 0.002692
97 Feces Saccharimonadaceae 0.002640 0.00482 0.001393
477 Solid Beijerinckiaceae 0.002619 0.00478 0.001381
478 Solid Beutenbergiaceae 0.002500 0.00689 0.001989
253 Liquid Strained Carnobacteriaceae 0.002454 0.00850 0.002454
288 Liquid Strained Leptotrichiaceae 0.002454 0.00850 0.002454
434 Liquid Unstrained Porphyromonadaceae 0.002452 0.00458 0.001618
548 Solid Planococcaceae 0.002440 0.00622 0.001795
132 Grab Sample Beijerinckiaceae 0.002372 0.00558 0.001611
240 Liquid Strained Bacteriovoracaceae 0.002319 0.00547 0.001578
448 Liquid Unstrained Spirosomaceae 0.001968 0.00557 0.001968
33 Feces Deferribacteraceae 0.001954 0.00677 0.001954
100 Feces Sphingobacteriaceae 0.001954 0.00677 0.001954
549 Solid Porphyromonadaceae 0.001854 0.00477 0.001378
539 Solid p-2534-18B5_gut_group 0.001850 0.00432 0.001248
514 Solid Hymenobacteraceae 0.001800 0.00421 0.001215
575 Solid Xanthomonadaceae 0.001800 0.00421 0.001215
255 Liquid Strained Cellvibrionaceae 0.001620 0.00437 0.001263
119 Grab Sample Aerococcaceae 0.001591 0.00551 0.001591
167 Grab Sample Fusobacteriaceae 0.001591 0.00551 0.001591
528 Solid Micrococcaceae 0.001587 0.00372 0.001074
124 Grab Sample Bacillaceae 0.001579 0.00547 0.001579
173 Grab Sample Leptotrichiaceae 0.001579 0.00547 0.001579
179 Grab Sample Methanocorpusculaceae 0.001579 0.00547 0.001579
399 Liquid Unstrained Hymenobacteraceae 0.001554 0.00440 0.001554
455 Liquid Unstrained Terasakiellaceae 0.001554 0.00440 0.001554
459 Liquid Unstrained Weeksellaceae 0.001554 0.00440 0.001554
482 Solid Cardiobacteriaceae 0.001517 0.00372 0.001075
333 Liquid Strained Spirosomaceae 0.001507 0.00522 0.001507
305 Liquid Strained Nocardioidaceae 0.001501 0.00398 0.001150
104 Feces Staphylococcaceae 0.001454 0.00504 0.001454
483 Solid Carnobacteriaceae 0.001437 0.00348 0.001006
74 Feces Nocardiaceae 0.001411 0.00330 0.000952
254 Liquid Strained Caulobacteraceae 0.001395 0.00364 0.001051
304 Liquid Strained Nocardiaceae 0.001395 0.00364 0.001051
77 Feces Oligosphaeraceae 0.001367 0.00474 0.001367
26 Feces Chitinophagaceae 0.001357 0.00470 0.001357
101 Feces Sphingomonadaceae 0.001357 0.00470 0.001357
190 Grab Sample Nocardioidaceae 0.001291 0.00447 0.001291
600 Stomach Tube Cellvibrionaceae 0.001285 0.00445 0.001285
650 Stomach Tube Nocardioidaceae 0.001285 0.00445 0.001285
290 Liquid Strained M2PB4-65_termite_group 0.001239 0.00429 0.001239
328 Liquid Strained Sanguibacteraceae 0.001239 0.00429 0.001239
593 Stomach Tube Beutenbergiaceae 0.001196 0.00414 0.001196
396 Liquid Unstrained Flavobacteriaceae 0.001090 0.00308 0.001090
400 Liquid Unstrained Kineosporiaceae 0.001090 0.00308 0.001090
133 Grab Sample Beutenbergiaceae 0.001054 0.00365 0.001054
138 Grab Sample Carnobacteriaceae 0.001054 0.00365 0.001054
204 Grab Sample Porphyromonadaceae 0.001054 0.00365 0.001054
219 Grab Sample Staphylococcaceae 0.001054 0.00365 0.001054
296 Liquid Strained Methanosarcinaceae 0.001015 0.00351 0.001015
319 Liquid Strained Porphyromonadaceae 0.001015 0.00351 0.001015
674 Stomach Tube Solirubrobacteraceae 0.000993 0.00344 0.000993
349 Liquid Unstrained Aerococcaceae 0.000984 0.00278 0.000984
369 Liquid Unstrained Caulobacteraceae 0.000984 0.00278 0.000984
370 Liquid Unstrained Cellvibrionaceae 0.000984 0.00278 0.000984
48 Feces Family_XI 0.000977 0.00339 0.000977
42 Feces Endomicrobiaceae 0.000968 0.00335 0.000968
98 Feces Sanguibacteraceae 0.000945 0.00327 0.000945
91 Feces Pseudomonadaceae 0.000930 0.00322 0.000930
115 Feces Xanthomonadaceae 0.000930 0.00322 0.000930
486 Solid Chitinophagaceae 0.000853 0.00296 0.000853
9 Feces Bacillaceae 0.000844 0.00292 0.000844
68 Feces Micrococcaceae 0.000844 0.00292 0.000844
72 Feces Neisseriaceae 0.000844 0.00292 0.000844
82 Feces Pasteurellaceae 0.000844 0.00292 0.000844
464 Solid Aerococcaceae 0.000826 0.00286 0.000826
469 Solid Bacillaceae 0.000826 0.00286 0.000826
526 Solid Methanosarcinaceae 0.000826 0.00286 0.000826
284 Liquid Strained Hymenobacteraceae 0.000762 0.00264 0.000762
309 Liquid Strained p-2534-18B5_gut_group 0.000762 0.00264 0.000762
38 Feces Devosiaceae 0.000727 0.00252 0.000727
107 Feces Synergistaceae 0.000727 0.00252 0.000727
54 Feces Hymenobacteraceae 0.000684 0.00237 0.000684
62 Feces Marinilabiliaceae 0.000684 0.00237 0.000684
76 Feces Oligoflexaceae 0.000684 0.00237 0.000684
570 Solid Terasakiellaceae 0.000650 0.00225 0.000650
542 Solid Pasteurellaceae 0.000534 0.00185 0.000534
563 Solid Spirosomaceae 0.000534 0.00185 0.000534
1 Feces 0319-6G20 0.000000 0.00000 0.000000
4 Feces Aerococcaceae 0.000000 0.00000 0.000000
10 Feces Bacteriovoracaceae 0.000000 0.00000 0.000000
15 Feces Bacteroidetes_BD2-2 0.000000 0.00000 0.000000
18 Feces Beutenbergiaceae 0.000000 0.00000 0.000000
22 Feces Cardiobacteriaceae 0.000000 0.00000 0.000000
23 Feces Carnobacteriaceae 0.000000 0.00000 0.000000
24 Feces Caulobacteraceae 0.000000 0.00000 0.000000
25 Feces Cellvibrionaceae 0.000000 0.00000 0.000000
30 Feces COB_P4-1_termite_group 0.000000 0.00000 0.000000
35 Feces Desulfobulbaceae 0.000000 0.00000 0.000000
37 Feces Desulfuromonadaceae 0.000000 0.00000 0.000000
39 Feces Dysgonomonadaceae 0.000000 0.00000 0.000000
51 Feces Flavobacteriaceae 0.000000 0.00000 0.000000
55 Feces Kineosporiaceae 0.000000 0.00000 0.000000
58 Feces Leptotrichiaceae 0.000000 0.00000 0.000000
59 Feces Leuconostocaceae 0.000000 0.00000 0.000000
60 Feces M2PB4-65_termite_group 0.000000 0.00000 0.000000
66 Feces Methanosarcinaceae 0.000000 0.00000 0.000000
69 Feces Moraxellaceae 0.000000 0.00000 0.000000
71 Feces Mycoplasmataceae 0.000000 0.00000 0.000000
75 Feces Nocardioidaceae 0.000000 0.00000 0.000000
83 Feces Pedosphaeraceae 0.000000 0.00000 0.000000
84 Feces PeH15 0.000000 0.00000 0.000000
89 Feces Porphyromonadaceae 0.000000 0.00000 0.000000
94 Feces Rhodobacteraceae 0.000000 0.00000 0.000000
99 Feces Solirubrobacteraceae 0.000000 0.00000 0.000000
103 Feces Spirosomaceae 0.000000 0.00000 0.000000
108 Feces Syntrophomonadaceae 0.000000 0.00000 0.000000
114 Feces Weeksellaceae 0.000000 0.00000 0.000000
117 Grab Sample Acetobacteraceae 0.000000 0.00000 0.000000
131 Grab Sample Barnesiellaceae 0.000000 0.00000 0.000000
134 Grab Sample Bifidobacteriaceae 0.000000 0.00000 0.000000
140 Grab Sample Cellvibrionaceae 0.000000 0.00000 0.000000
141 Grab Sample Chitinophagaceae 0.000000 0.00000 0.000000
148 Grab Sample Deferribacteraceae 0.000000 0.00000 0.000000
154 Grab Sample Dysgonomonadaceae 0.000000 0.00000 0.000000
166 Grab Sample Flavobacteriaceae 0.000000 0.00000 0.000000
168 Grab Sample GZKB124 0.000000 0.00000 0.000000
169 Grab Sample Hymenobacteraceae 0.000000 0.00000 0.000000
170 Grab Sample Kineosporiaceae 0.000000 0.00000 0.000000
181 Grab Sample Methanosarcinaceae 0.000000 0.00000 0.000000
183 Grab Sample Micrococcaceae 0.000000 0.00000 0.000000
187 Grab Sample Neisseriaceae 0.000000 0.00000 0.000000
188 Grab Sample Nitrosomonadaceae 0.000000 0.00000 0.000000
192 Grab Sample Oligosphaeraceae 0.000000 0.00000 0.000000
194 Grab Sample p-2534-18B5_gut_group 0.000000 0.00000 0.000000
214 Grab Sample Solirubrobacteraceae 0.000000 0.00000 0.000000
225 Grab Sample Terasakiellaceae 0.000000 0.00000 0.000000
229 Grab Sample Weeksellaceae 0.000000 0.00000 0.000000
232 Liquid Strained Acetobacteraceae 0.000000 0.00000 0.000000
246 Liquid Strained Barnesiellaceae 0.000000 0.00000 0.000000
248 Liquid Strained Beutenbergiaceae 0.000000 0.00000 0.000000
256 Liquid Strained Chitinophagaceae 0.000000 0.00000 0.000000
263 Liquid Strained Deferribacteraceae 0.000000 0.00000 0.000000
269 Liquid Strained Dysgonomonadaceae 0.000000 0.00000 0.000000
281 Liquid Strained Flavobacteriaceae 0.000000 0.00000 0.000000
283 Liquid Strained GZKB124 0.000000 0.00000 0.000000
285 Liquid Strained Kineosporiaceae 0.000000 0.00000 0.000000
303 Liquid Strained Nitrosomonadaceae 0.000000 0.00000 0.000000
307 Liquid Strained Oligosphaeraceae 0.000000 0.00000 0.000000
329 Liquid Strained Solirubrobacteraceae 0.000000 0.00000 0.000000
344 Liquid Strained Weeksellaceae 0.000000 0.00000 0.000000
347 Liquid Unstrained Acetobacteraceae 0.000000 0.00000 0.000000
354 Liquid Unstrained Bacillaceae 0.000000 0.00000 0.000000
355 Liquid Unstrained Bacteriovoracaceae 0.000000 0.00000 0.000000
361 Liquid Unstrained Barnesiellaceae 0.000000 0.00000 0.000000
363 Liquid Unstrained Beutenbergiaceae 0.000000 0.00000 0.000000
368 Liquid Unstrained Carnobacteriaceae 0.000000 0.00000 0.000000
371 Liquid Unstrained Chitinophagaceae 0.000000 0.00000 0.000000
378 Liquid Unstrained Deferribacteraceae 0.000000 0.00000 0.000000
398 Liquid Unstrained GZKB124 0.000000 0.00000 0.000000
403 Liquid Unstrained Leptotrichiaceae 0.000000 0.00000 0.000000
411 Liquid Unstrained Methanosarcinaceae 0.000000 0.00000 0.000000
418 Liquid Unstrained Nitrosomonadaceae 0.000000 0.00000 0.000000
420 Liquid Unstrained Nocardioidaceae 0.000000 0.00000 0.000000
422 Liquid Unstrained Oligosphaeraceae 0.000000 0.00000 0.000000
424 Liquid Unstrained p-2534-18B5_gut_group 0.000000 0.00000 0.000000
444 Liquid Unstrained Solirubrobacteraceae 0.000000 0.00000 0.000000
462 Solid Acetobacteraceae 0.000000 0.00000 0.000000
476 Solid Barnesiellaceae 0.000000 0.00000 0.000000
485 Solid Cellvibrionaceae 0.000000 0.00000 0.000000
493 Solid Deferribacteraceae 0.000000 0.00000 0.000000
511 Solid Flavobacteriaceae 0.000000 0.00000 0.000000
513 Solid GZKB124 0.000000 0.00000 0.000000
515 Solid Kineosporiaceae 0.000000 0.00000 0.000000
518 Solid Leptotrichiaceae 0.000000 0.00000 0.000000
532 Solid Neisseriaceae 0.000000 0.00000 0.000000
533 Solid Nitrosomonadaceae 0.000000 0.00000 0.000000
535 Solid Nocardioidaceae 0.000000 0.00000 0.000000
537 Solid Oligosphaeraceae 0.000000 0.00000 0.000000
559 Solid Solirubrobacteraceae 0.000000 0.00000 0.000000
574 Solid Weeksellaceae 0.000000 0.00000 0.000000
577 Stomach Tube Acetobacteraceae 0.000000 0.00000 0.000000
585 Stomach Tube Bacteriovoracaceae 0.000000 0.00000 0.000000
591 Stomach Tube Barnesiellaceae 0.000000 0.00000 0.000000
601 Stomach Tube Chitinophagaceae 0.000000 0.00000 0.000000
608 Stomach Tube Deferribacteraceae 0.000000 0.00000 0.000000
614 Stomach Tube Dysgonomonadaceae 0.000000 0.00000 0.000000
626 Stomach Tube Flavobacteriaceae 0.000000 0.00000 0.000000
628 Stomach Tube GZKB124 0.000000 0.00000 0.000000
629 Stomach Tube Hymenobacteraceae 0.000000 0.00000 0.000000
630 Stomach Tube Kineosporiaceae 0.000000 0.00000 0.000000
641 Stomach Tube Methanosarcinaceae 0.000000 0.00000 0.000000
648 Stomach Tube Nitrosomonadaceae 0.000000 0.00000 0.000000
652 Stomach Tube Oligosphaeraceae 0.000000 0.00000 0.000000
654 Stomach Tube p-2534-18B5_gut_group 0.000000 0.00000 0.000000
669 Stomach Tube Rhodobacteraceae 0.000000 0.00000 0.000000
678 Stomach Tube Spirosomaceae 0.000000 0.00000 0.000000
685 Stomach Tube Terasakiellaceae 0.000000 0.00000 0.000000
689 Stomach Tube Weeksellaceae 0.000000 0.00000 0.000000

These are the families found in all samples sorted by decending order of mean relative abundance. Next we will graph out some of the different fam based on their abundance ranges.

We will have a closer look at the familes present in fecal samples.

These are the relative abundance of families found in fecal samples. Next we will graph out these families.

Intially, we can see that there is more Bacteroidaceae and Peptostreptococcaceae in fecal samples compared to rumen samples.

Sample_Type Family mean sd sem
1 Feces Bacteroidaceae 7.4037510 0.8711443 0.2514777
14 Grab Sample Bacteroidaceae 0.0355318 0.0298742 0.0086239
27 Liquid Strained Bacteroidaceae 0.0376197 0.0385991 0.0111426
40 Liquid Unstrained Bacteroidaceae 0.0499720 0.0397877 0.0140671
53 Solid Bacteroidaceae 0.0275221 0.0236625 0.0068308
66 Stomach Tube Bacteroidaceae 0.0710867 0.1147546 0.0331268
Sample_Type Family mean sd sem
8 Feces Peptostreptococcaceae 2.8945224 0.8990991 0.2595475
21 Grab Sample Peptostreptococcaceae 0.0273192 0.0178096 0.0051412
34 Liquid Strained Peptostreptococcaceae 0.0365307 0.0322717 0.0093160
47 Liquid Unstrained Peptostreptococcaceae 0.0322039 0.0175574 0.0062075
60 Solid Peptostreptococcaceae 0.0327935 0.0206118 0.0059501
73 Stomach Tube Peptostreptococcaceae 0.0435303 0.0159367 0.0046005

Conversely, there is more Veillonellaceae and Fibrobacteraceae in rumen samples compared to feces.

Sample_Type Family mean sd sem
13 Feces Veillonellaceae 0.0031847 0.0059171 0.0017081
26 Grab Sample Veillonellaceae 0.7480463 0.1859221 0.0536711
39 Liquid Strained Veillonellaceae 2.1133656 0.5698565 0.1645034
52 Liquid Unstrained Veillonellaceae 1.5589519 0.8019100 0.2835180
65 Solid Veillonellaceae 0.3685489 0.1024515 0.0295752
78 Stomach Tube Veillonellaceae 0.6770020 0.4122323 0.1190012
Sample_Type Family mean sd sem
5 Feces Fibrobacteraceae 0.0186986 0.0180463 0.0052095
18 Grab Sample Fibrobacteraceae 2.2866939 0.5464401 0.1577437
31 Liquid Strained Fibrobacteraceae 2.0179385 0.7904481 0.2281827
44 Liquid Unstrained Fibrobacteraceae 1.0178780 0.6578643 0.2325902
57 Solid Fibrobacteraceae 1.5059297 0.6251762 0.1804728
70 Stomach Tube Fibrobacteraceae 0.3770986 0.2593853 0.0748781

I will make an interactive bubble graph for the lower families

Next we are going to do some exploratory analysis of all sample types.

Archaea Populations

Now we will take a closer look at the Archeaon populations.

## [1] "These are the Classes in the Kingdom Archaea found in all sample types"
## [1] "Methanobacteria" "Thermoplasmata"  "Methanomicrobia"
## [1] "These are the Orders in the Kingdom Archaea found in all sample types"
## [1] "Methanobacteriales"      "Methanomassiliicoccales"
## [3] "Methanosarcinales"       "Methanomicrobiales"
## [1] "These are the Families in the Kingdom Archaea found in all sample types"
## [1] "Methanobacteriaceae"     "Methanomethylophilaceae"
## [3] "Methanosarcinaceae"      "Methanocorpusculaceae"
## [1] "These are the Genera in the Kingdom Archaea found in all sample types"
## [1] NA                                "Methanobrevibacter"             
## [3] "Methanosphaera"                  "Candidatus_Methanomethylophilus"
## [5] "Methanimicrococcus"              "Methanocorpusculum"
## [1] "These are the Species in the Kingdom Archaea found in all sample types"
## [1] NA

Looking at the relative abundances of archaeal genera in all samples.

Statistiscs for Abundance of Archaea Genera Across all Sample Types
Sample_Type Genus mean sd sem
13 Liquid Strained Methanobrevibacter 94.3304 2.7636 0.7978
18 Liquid Unstrained Methanobrevibacter 91.9836 2.4326 0.8600
28 Stomach Tube Methanobrevibacter 90.6458 2.8016 0.8088
8 Grab Sample Methanobrevibacter 88.8381 3.0998 0.8948
23 Solid Methanobrevibacter 87.1990 6.2745 1.8113
3 Feces Methanobrevibacter 82.6272 13.4013 3.8686
4 Feces Methanocorpusculum 13.8867 13.1204 3.7875
25 Solid Methanosphaera 12.3900 5.6762 1.6386
10 Grab Sample Methanosphaera 10.9553 3.0536 0.8815
30 Stomach Tube Methanosphaera 9.0903 2.9570 0.8536
20 Liquid Unstrained Methanosphaera 6.5510 2.5410 0.8984
15 Liquid Strained Methanosphaera 5.1476 2.8505 0.8229
5 Feces Methanosphaera 3.4862 4.7416 1.3688
16 Liquid Unstrained Candidatus_Methanomethylophilus 1.2983 1.2264 0.4336
24 Solid Methanocorpusculum 0.3248 0.7518 0.2170
11 Liquid Strained Candidatus_Methanomethylophilus 0.2623 0.5970 0.1724
14 Liquid Strained Methanocorpusculum 0.2010 0.3275 0.0945
19 Liquid Unstrained Methanocorpusculum 0.1670 0.3097 0.1095
29 Stomach Tube Methanocorpusculum 0.1416 0.2746 0.0793
6 Grab Sample Candidatus_Methanomethylophilus 0.1366 0.4732 0.1366
26 Stomach Tube Candidatus_Methanomethylophilus 0.1222 0.3278 0.0946
9 Grab Sample Methanocorpusculum 0.0700 0.2426 0.0700
21 Solid Candidatus_Methanomethylophilus 0.0678 0.2347 0.0678
12 Liquid Strained Methanimicrococcus 0.0587 0.2033 0.0587
22 Solid Methanimicrococcus 0.0184 0.0636 0.0184
1 Feces Candidatus_Methanomethylophilus 0.0000 0.0000 0.0000
2 Feces Methanimicrococcus 0.0000 0.0000 0.0000
7 Grab Sample Methanimicrococcus 0.0000 0.0000 0.0000
17 Liquid Unstrained Methanimicrococcus 0.0000 0.0000 0.0000
27 Stomach Tube Methanimicrococcus 0.0000 0.0000 0.0000

Next we will check if there are certain archeal genera that are found in common between fecal and rumen samples. We will also look to see if there are differences between these two sample types.

## [1] "These taxa are found in both phyloseq objects"
## [1] "Methanobacteriaceae"   "Methanocorpusculaceae"
## [1] "These taxa are different between the phyloseq objects"
## [1] "Methanomethylophilaceae" "Methanosarcinaceae"

Next, we look at the relative abundances of genera in rumen samples.

Statistiscs for Abundance of Archaea Genera
Sample_Type Genus mean sd sem
8 Liquid Strained Methanobrevibacter 94.3304 2.7636 0.7978
13 Liquid Unstrained Methanobrevibacter 91.9836 2.4326 0.8600
23 Stomach Tube Methanobrevibacter 90.6458 2.8016 0.8088
3 Grab Sample Methanobrevibacter 88.8381 3.0998 0.8948
18 Solid Methanobrevibacter 87.1990 6.2745 1.8113
20 Solid Methanosphaera 12.3900 5.6762 1.6386
5 Grab Sample Methanosphaera 10.9553 3.0536 0.8815
25 Stomach Tube Methanosphaera 9.0903 2.9570 0.8536
15 Liquid Unstrained Methanosphaera 6.5510 2.5410 0.8984
10 Liquid Strained Methanosphaera 5.1476 2.8505 0.8229
11 Liquid Unstrained Candidatus_Methanomethylophilus 1.2983 1.2264 0.4336
19 Solid Methanocorpusculum 0.3248 0.7518 0.2170
6 Liquid Strained Candidatus_Methanomethylophilus 0.2623 0.5970 0.1724
9 Liquid Strained Methanocorpusculum 0.2010 0.3275 0.0945
14 Liquid Unstrained Methanocorpusculum 0.1670 0.3097 0.1095
24 Stomach Tube Methanocorpusculum 0.1416 0.2746 0.0793
1 Grab Sample Candidatus_Methanomethylophilus 0.1366 0.4732 0.1366
21 Stomach Tube Candidatus_Methanomethylophilus 0.1222 0.3278 0.0946
4 Grab Sample Methanocorpusculum 0.0700 0.2426 0.0700
16 Solid Candidatus_Methanomethylophilus 0.0678 0.2347 0.0678
7 Liquid Strained Methanimicrococcus 0.0587 0.2033 0.0587
17 Solid Methanimicrococcus 0.0184 0.0636 0.0184
2 Grab Sample Methanimicrococcus 0.0000 0.0000 0.0000
12 Liquid Unstrained Methanimicrococcus 0.0000 0.0000 0.0000
22 Stomach Tube Methanimicrococcus 0.0000 0.0000 0.0000

We will do the same for fecal samples.

Statistiscs for Abundance of Archaea Genera
Sample_Type Genus mean sd sem
Feces Methanobrevibacter 82.63 13.40 3.87
Feces Methanocorpusculum 13.89 13.12 3.79
Feces Methanosphaera 3.49 4.74 1.37

Unsupervised exploratory analysis

Going to use log transformations for normalizing for library size during exploratory analysis. As this looks appropriate for the “tailed” data. For additional confirmation we could do a the same analysis on ranked values for abundance.

## Saving 7 x 5 in image

The fecal samples pull away from the other samples on the first axis. Liquid strained and unstrained samples move higher on the 2nd axis, but this difference is 1/5th that of the differences between fecal samples and all other samples. Overall, it appears that there is 2-3 “clusters”. Next we will ordinate unifrac distances which will take into account phylogenetic differeces in differences in samples.

From the eigenvalues we can see that 2 axis is appropriate for graphing, together explaining 86.7954988% of the variance between the samples.

This is Figure 3. We will calculate the gap statisitic to determine how many clusters are here.

The gap statistic strongly suggests at least three clusters, but makes another big jump at K=5 before the slope levels. So, K=5 it is. We had 6 sample types so this suggests 2 of the sample types are basically the same.

Now that we take into account phylogenetic information in the distance metric we see a similar clustering pattern as with the bray-curtis. However, now the difference between fecal and other samples on the 1st axis explain 66.5% of the variation. Also, although not quite as clean there still seems to be 3 “clusters”. If you didn’t have stomach tube samples this would be more clear. Grab sample and solid samples aren’t very different from each other.

For good measure we will look at the unweighted unifrac that puts more weight on rare species as well.

We’ll first let’s check on the eigenvalues.

The eigenvalues here show 2 axis are sufficient to capture most of the total variation.

This gives a similar pattern as the bray-curtis and weighted unifrac. Notice that less of the variation is explained in each axis with the unweighted (total 52.7%) versus the weighted unifrac. The fecal samples are clustered closer together than with the weighted unifrac. Again, we will look at the gap statistic.

Just as before, the gap statistic strongly suggests at least three clusters, but makes another big jump at K=5 before the slope levels. So, K=5 it is. We had 6 sample types so this suggests 2 of the sample types are basically the same.

Another way to comparing phylogentic differences is double principal coordinates analysis (DPCoA), which is a phylogenetic ordination method and that provides a biplot representation of both samples and taxonomic categories. The computational time for this is much longer than with the unifrac (i.e. Has to be run on a server).

The eigenvalues here show 2 axis are sufficient to capture most of the total variation.

We see again that the 1st axis corresponds to Rumen vs.fecal samples, while the 2nd axis distinguishes Liquid preparations vs those that get liquid and solid fractions. The biplot suggests that the 1st axis can be interpreted to say: samples that have larger scores on the first axis have a subset of taxa from Bacteroidetes and subset of Firmicutes that is different than rumen samples. Additionally, Liquid samples have more Bacteroidetes and less Firmicutes than other rumen sample types. Liquid strained samples are being pulled down on the 2nd axis by Kiritimatiellaeota and a subset of Bacteroidetes.

Again, I have made an interactive Version of this plot that is avaliable here.

Since Firmicutes and Bacteroidetes take up so much of the graph we want to know what other phyla can separate the sample types.

Again, I have made an interactive Version of this plot that is avaliable here.

Now that we have Firmicutes and Bacteroidetes gone we can see that feces are associated with Akkermansiaceae and isn’t associated with Kiritimatiellaeota, Chloroflexi, Fibrobacteraceae and Spirochaetaceae.

Shared ASVs between sample types.

Liquid unstrained samples have 510 ASVs in common. Liquid strained samples have 307 ASVs in common. Samples from feces have 441 ASVs in common with one another. Soild samples have 405 ASVs in common. Samples from a stomach tube have 255 ASVs in common. Grab samples have 319 ASVs in common.

Differential Abundance Testing

Corncob: Grab sample vs all other sample types

First we will look at how the “gold standard” grab sample compares to other sample types. We test all the taxa in our data to see if they are differentially-abundant. The differentialTest function will these tests on all taxa, while controlling the false discovery rate to account for multiple comparisons. Addtionally, it controls for differencs in library sizes.

We will take a broad view and look at phyla that are differentially abundant

Looking at the models from corncob.

## $Bacteria_Tenericutes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -4.32618    0.08935 -48.418  < 2e-16 ***
## Sample_TypeFeces             -0.32385    0.09904  -3.270 0.001844 ** 
## Sample_TypeStomach Tube       0.14483    0.09009   1.608 0.113558    
## Sample_TypeLiquid Strained    0.41839    0.08479   4.934 7.58e-06 ***
## Sample_TypeLiquid Unstrained  0.35318    0.09588   3.684 0.000519 ***
## Sample_TypeSolid             -0.20922    0.09627  -2.173 0.034002 *  
## CowIDCow_2477                 0.11394    0.07278   1.566 0.123058    
## CowIDCow_2549                 0.02563    0.07502   0.342 0.733939    
## CowIDCow_796                 -0.05018    0.07647  -0.656 0.514415    
## DayDay_7                      0.02400    0.06693   0.359 0.721206    
## DayDay_9                     -0.01661    0.06224  -0.267 0.790558    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -7.5406     0.2152  -35.04   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -307.82
## 
## $Bacteria_Kiritimatiellaeota
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -4.66083    0.14790 -31.514  < 2e-16 ***
## Sample_TypeFeces             -0.19514    0.18212  -1.071 0.288551    
## Sample_TypeStomach Tube       0.55100    0.15792   3.489 0.000951 ***
## Sample_TypeLiquid Strained    1.98774    0.13439  14.791  < 2e-16 ***
## Sample_TypeLiquid Unstrained  1.31125    0.15124   8.670 6.19e-12 ***
## Sample_TypeSolid             -0.15332    0.17998  -0.852 0.397920    
## CowIDCow_2477                 0.09767    0.09331   1.047 0.299717    
## CowIDCow_2549                -0.14153    0.09935  -1.425 0.159826    
## CowIDCow_796                 -0.29557    0.10239  -2.887 0.005520 ** 
## DayDay_7                      0.08338    0.09483   0.879 0.382986    
## DayDay_9                      0.36822    0.08184   4.499 3.49e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -6.2890     0.1865  -33.72   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -349.59
## 
## $Bacteria_Verrucomicrobia
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -5.860455   0.145912 -40.164  < 2e-16 ***
## Sample_TypeFeces              1.340823   0.130015  10.313 1.48e-14 ***
## Sample_TypeStomach Tube       0.591455   0.144743   4.086 0.000141 ***
## Sample_TypeLiquid Strained    0.159528   0.156768   1.018 0.313242    
## Sample_TypeLiquid Unstrained  0.451235   0.161794   2.789 0.007212 ** 
## Sample_TypeSolid              0.052724   0.157616   0.335 0.739247    
## CowIDCow_2477                 0.248618   0.105124   2.365 0.021520 *  
## CowIDCow_2549                 0.169063   0.109513   1.544 0.128275    
## CowIDCow_796                  0.316604   0.104636   3.026 0.003741 ** 
## DayDay_7                     -0.027690   0.091791  -0.302 0.764025    
## DayDay_9                      0.005016   0.086490   0.058 0.953961    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -7.8166     0.2357  -33.16   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -266.88
## 
## $Bacteria_Epsilonbacteraeota
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -10.51920    0.75370 -13.957  < 2e-16 ***
## Sample_TypeFeces               2.59059    0.72991   3.549 0.000791 ***
## Sample_TypeStomach Tube        1.84208    0.77336   2.382 0.020646 *  
## Sample_TypeLiquid Strained     1.90205    0.76235   2.495 0.015572 *  
## Sample_TypeLiquid Unstrained   0.52436    0.87565   0.599 0.551702    
## Sample_TypeSolid               0.85753    0.80476   1.066 0.291193    
## CowIDCow_2477                  0.75178    0.28370   2.650 0.010444 *  
## CowIDCow_2549                 -0.07158    0.36864  -0.194 0.846743    
## CowIDCow_796                  -0.53520    0.40013  -1.338 0.186442    
## DayDay_7                      -0.53806    0.29915  -1.799 0.077466 .  
## DayDay_9                       0.07371    0.25463   0.289 0.773277    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -11.474      2.969  -3.865 0.000291 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -80.421
## 
## $Bacteria_Elusimicrobia
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -6.97333    0.20177 -34.561  < 2e-16 ***
## Sample_TypeFeces             -0.09038    0.22702  -0.398    0.692    
## Sample_TypeStomach Tube       0.34659    0.21366   1.622    0.110    
## Sample_TypeLiquid Strained    1.20583    0.18644   6.468 2.61e-08 ***
## Sample_TypeLiquid Unstrained  0.95436    0.20218   4.720 1.62e-05 ***
## Sample_TypeSolid              0.30858    0.20944   1.473    0.146    
## CowIDCow_2477                 0.58131    0.13758   4.225 8.88e-05 ***
## CowIDCow_2549                 0.03532    0.15654   0.226    0.822    
## CowIDCow_796                 -0.12122    0.16197  -0.748    0.457    
## DayDay_7                     -0.17256    0.13773  -1.253    0.215    
## DayDay_9                      0.17873    0.11616   1.539    0.130    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -8.4564     0.2785  -30.37   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -210.21
## 
## $Bacteria_Planctomycetes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -6.95287    0.15019 -46.295  < 2e-16 ***
## Sample_TypeFeces              0.69873    0.14002   4.990  6.2e-06 ***
## Sample_TypeStomach Tube       0.28194    0.15811   1.783   0.0800 .  
## Sample_TypeLiquid Strained   -0.30166    0.17245  -1.749   0.0857 .  
## Sample_TypeLiquid Unstrained -0.06845    0.17834  -0.384   0.7026    
## Sample_TypeSolid              0.10523    0.15201   0.692   0.4916    
## CowIDCow_2477                -0.13631    0.11419  -1.194   0.2376    
## CowIDCow_2549                 0.07430    0.11610   0.640   0.5248    
## CowIDCow_796                  0.11625    0.11074   1.050   0.2984    
## DayDay_7                     -0.07950    0.10021  -0.793   0.4309    
## DayDay_9                     -0.03517    0.09700  -0.363   0.7183    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -18.02      49.49  -0.364    0.717
## 
## 
## Log-likelihood: -163.02
## 
## $Bacteria_Patescibacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -5.22958    0.10429 -50.144  < 2e-16 ***
## Sample_TypeFeces             -4.33629    0.50006  -8.672 6.15e-12 ***
## Sample_TypeStomach Tube      -0.38750    0.11263  -3.440  0.00110 ** 
## Sample_TypeLiquid Strained   -0.06420    0.10112  -0.635  0.52807    
## Sample_TypeLiquid Unstrained  0.06616    0.11269   0.587  0.55949    
## Sample_TypeSolid              0.29885    0.09132   3.273  0.00183 ** 
## CowIDCow_2477                -0.13598    0.09056  -1.502  0.13884    
## CowIDCow_2549                -0.23319    0.09478  -2.460  0.01699 *  
## CowIDCow_796                  0.13796    0.08702   1.585  0.11850    
## DayDay_7                      0.17327    0.07951   2.179  0.03353 *  
## DayDay_9                     -0.06957    0.07835  -0.888  0.37837    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -8.738      0.343  -25.47   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -213.52
## 
## $Bacteria_Proteobacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -4.34791    0.11118 -39.107  < 2e-16 ***
## Sample_TypeFeces             -0.41730    0.12915  -3.231 0.002068 ** 
## Sample_TypeStomach Tube       0.12531    0.11381   1.101 0.275561    
## Sample_TypeLiquid Strained    0.91226    0.09900   9.215 8.13e-13 ***
## Sample_TypeLiquid Unstrained  0.54359    0.11377   4.778 1.32e-05 ***
## Sample_TypeSolid             -0.03213    0.11691  -0.275 0.784479    
## CowIDCow_2477                 0.45601    0.08564   5.325 1.85e-06 ***
## CowIDCow_2549                 0.32237    0.08849   3.643 0.000591 ***
## CowIDCow_796                 -0.13856    0.09773  -1.418 0.161787    
## DayDay_7                     -0.13382    0.08325  -1.607 0.113582    
## DayDay_9                      0.23357    0.07003   3.335 0.001517 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -6.7521     0.1918   -35.2   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -339.24
## 
## $Bacteria_Fusobacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -9.40842    0.72991 -12.890  < 2e-16 ***
## Sample_TypeFeces              0.02635    0.91483   0.029 0.977121    
## Sample_TypeStomach Tube       3.80213    0.72825   5.221  2.7e-06 ***
## Sample_TypeLiquid Strained    0.66197    0.82281   0.805 0.424494    
## Sample_TypeLiquid Unstrained  0.62044    0.98151   0.632 0.529877    
## Sample_TypeSolid              0.42278    0.86887   0.487 0.628449    
## CowIDCow_2477                -0.79047    0.26869  -2.942 0.004737 ** 
## CowIDCow_2549                -0.88565    0.27579  -3.211 0.002190 ** 
## CowIDCow_796                 -0.55192    0.27870  -1.980 0.052587 .  
## DayDay_7                     -0.97230    0.24566  -3.958 0.000215 ***
## DayDay_9                     -1.00289    0.27730  -3.617 0.000641 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -10.465      1.562  -6.698 1.09e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -76.012
## 
## $Archaea_Euryarchaeota
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -3.36934    0.14166 -23.784  < 2e-16 ***
## Sample_TypeFeces             -1.37244    0.21409  -6.411 3.24e-08 ***
## Sample_TypeStomach Tube       0.27843    0.13998   1.989  0.05159 .  
## Sample_TypeLiquid Strained   -0.16155    0.15362  -1.052  0.29751    
## Sample_TypeLiquid Unstrained -0.23238    0.18171  -1.279  0.20623    
## Sample_TypeSolid              0.19658    0.14210   1.383  0.17205    
## CowIDCow_2477                -0.39646    0.13020  -3.045  0.00354 ** 
## CowIDCow_2549                -0.64312    0.14188  -4.533 3.11e-05 ***
## CowIDCow_796                  0.03754    0.11753   0.319  0.75060    
## DayDay_7                     -0.02151    0.11568  -0.186  0.85317    
## DayDay_9                     -0.09570    0.11006  -0.870  0.38826    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -5.6966     0.1806  -31.55   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -373.86
## 
## $Bacteria_Spirochaetes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -3.60125    0.23700 -15.195  < 2e-16 ***
## Sample_TypeFeces             -1.53490    0.30187  -5.085 4.42e-06 ***
## Sample_TypeStomach Tube      -0.83674    0.26859  -3.115  0.00290 ** 
## Sample_TypeLiquid Strained   -0.16348    0.22976  -0.712  0.47971    
## Sample_TypeLiquid Unstrained -0.27352    0.27019  -1.012  0.31573    
## Sample_TypeSolid             -0.72480    0.25765  -2.813  0.00675 ** 
## CowIDCow_2477                 0.06750    0.22101   0.305  0.76119    
## CowIDCow_2549                 0.22085    0.22116   0.999  0.32230    
## CowIDCow_796                 -0.20800    0.23062  -0.902  0.37095    
## DayDay_7                      0.20597    0.20392   1.010  0.31680    
## DayDay_9                      0.08773    0.18761   0.468  0.64189    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -4.662      0.187  -24.94   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -386.64
## 
## $Bacteria_Lentisphaerae
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                   -7.0354     0.2514 -27.987  < 2e-16 ***
## Sample_TypeFeces               0.8589     0.2691   3.191  0.00232 ** 
## Sample_TypeStomach Tube        1.5299     0.2498   6.125 9.52e-08 ***
## Sample_TypeLiquid Strained     2.0078     0.2404   8.353 2.04e-11 ***
## Sample_TypeLiquid Unstrained   1.9137     0.2545   7.519 4.79e-10 ***
## Sample_TypeSolid              -0.1782     0.3163  -0.563  0.57539    
## CowIDCow_2477                  0.2979     0.1344   2.217  0.03073 *  
## CowIDCow_2549                 -0.3844     0.1600  -2.403  0.01959 *  
## CowIDCow_796                  -0.3786     0.1589  -2.383  0.02061 *  
## DayDay_7                       0.1512     0.1390   1.088  0.28111    
## DayDay_9                       0.2184     0.1219   1.791  0.07865 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -7.593      0.225  -33.74   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -239.06
## 
## $Bacteria_Cyanobacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -6.677072   0.203395 -32.828  < 2e-16 ***
## Sample_TypeFeces              1.084069   0.195841   5.535 8.55e-07 ***
## Sample_TypeStomach Tube       0.553285   0.216712   2.553   0.0134 *  
## Sample_TypeLiquid Strained    1.780932   0.185392   9.606 1.92e-13 ***
## Sample_TypeLiquid Unstrained  1.338819   0.204092   6.560 1.84e-08 ***
## Sample_TypeSolid             -0.487660   0.262533  -1.858   0.0685 .  
## CowIDCow_2477                 0.623051   0.120964   5.151 3.48e-06 ***
## CowIDCow_2549                -0.146135   0.144215  -1.013   0.3153    
## CowIDCow_796                  0.009669   0.138073   0.070   0.9444    
## DayDay_7                     -0.098718   0.119096  -0.829   0.4107    
## DayDay_9                      0.139419   0.103197   1.351   0.1821    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -7.7710     0.2329  -33.36   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -245.28
## 
## $Bacteria_Actinobacteria
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -4.37305    0.09241 -47.323  < 2e-16 ***
## Sample_TypeFeces             -0.99467    0.12296  -8.089 5.51e-11 ***
## Sample_TypeStomach Tube       0.37822    0.08711   4.342 5.98e-05 ***
## Sample_TypeLiquid Strained   -0.47105    0.10640  -4.427 4.47e-05 ***
## Sample_TypeLiquid Unstrained -0.14511    0.11206  -1.295    0.201    
## Sample_TypeSolid              0.11323    0.09073   1.248    0.217    
## CowIDCow_2477                 0.06229    0.08059   0.773    0.443    
## CowIDCow_2549                -0.01023    0.08326  -0.123    0.903    
## CowIDCow_796                 -0.06658    0.08437  -0.789    0.433    
## DayDay_7                     -0.07041    0.07052  -0.998    0.322    
## DayDay_9                     -0.33301    0.07136  -4.666 1.95e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   -7.758      0.228  -34.03   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -286.95
## 
## $Bacteria_Fibrobacteres
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -3.85541    0.12869 -29.960  < 2e-16 ***
## Sample_TypeFeces             -3.66382    0.34094 -10.746 3.16e-15 ***
## Sample_TypeStomach Tube      -1.79490    0.19964  -8.991 1.87e-12 ***
## Sample_TypeLiquid Strained   -0.20619    0.12115  -1.702 0.094304 .  
## Sample_TypeLiquid Unstrained -0.95051    0.17339  -5.482 1.04e-06 ***
## Sample_TypeSolid             -0.44792    0.12854  -3.485 0.000965 ***
## CowIDCow_2477                 0.20363    0.12806   1.590 0.117426    
## CowIDCow_2549                 0.04339    0.13403   0.324 0.747362    
## CowIDCow_796                 -0.06200    0.13730  -0.452 0.653342    
## DayDay_7                     -0.09475    0.12010  -0.789 0.433470    
## DayDay_9                      0.09135    0.11044   0.827 0.411705    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -6.4614     0.2001  -32.28   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -297.24
## 
## $Bacteria_Chloroflexi
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -5.16680    0.08413 -61.413  < 2e-16 ***
## Sample_TypeFeces             -2.84256    0.21915 -12.971  < 2e-16 ***
## Sample_TypeStomach Tube       0.14863    0.08110   1.833  0.07217 .  
## Sample_TypeLiquid Strained   -0.29404    0.08904  -3.302  0.00167 ** 
## Sample_TypeLiquid Unstrained -0.01259    0.09335  -0.135  0.89320    
## Sample_TypeSolid              0.17696    0.07707   2.296  0.02544 *  
## CowIDCow_2477                 0.03086    0.07226   0.427  0.67099    
## CowIDCow_2549                -0.06050    0.07532  -0.803  0.42522    
## CowIDCow_796                  0.06224    0.07387   0.843  0.40307    
## DayDay_7                      0.08942    0.06434   1.390  0.17010    
## DayDay_9                     -0.04975    0.06268  -0.794  0.43073    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -9.3891     0.4459  -21.05   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -223.85
## 
## $Bacteria_Synergistetes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -7.54350    0.19936 -37.839  < 2e-16 ***
## Sample_TypeFeces             -4.39512    1.00931  -4.355 5.73e-05 ***
## Sample_TypeStomach Tube      -0.36401    0.20607  -1.767  0.08276 .  
## Sample_TypeLiquid Strained   -0.51760    0.20678  -2.503  0.01526 *  
## Sample_TypeLiquid Unstrained -0.56557    0.22408  -2.524  0.01447 *  
## Sample_TypeSolid              0.46773    0.16073   2.910  0.00518 ** 
## CowIDCow_2477                 0.42127    0.16165   2.606  0.01171 *  
## CowIDCow_2549                 0.38915    0.16631   2.340  0.02288 *  
## CowIDCow_796                 -0.11407    0.18717  -0.609  0.54469    
## DayDay_7                      0.05518    0.14853   0.372  0.71167    
## DayDay_9                      0.35590    0.13760   2.586  0.01233 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -18.02      67.71  -0.266    0.791
## 
## 
## Log-likelihood: -123.07
## 
## $Bacteria_Firmicutes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                   0.690866   0.080250   8.609 7.78e-12 ***
## Sample_TypeFeces             -0.131144   0.082612  -1.587 0.118038    
## Sample_TypeStomach Tube       0.021783   0.083320   0.261 0.794714    
## Sample_TypeLiquid Strained   -0.847284   0.081895 -10.346 1.31e-14 ***
## Sample_TypeLiquid Unstrained -0.377057   0.092779  -4.064 0.000152 ***
## Sample_TypeSolid              0.122158   0.084022   1.454 0.151558    
## CowIDCow_2477                -0.131287   0.068888  -1.906 0.061814 .  
## CowIDCow_2549                -0.088555   0.069290  -1.278 0.206511    
## CowIDCow_796                 -0.007342   0.069413  -0.106 0.916143    
## DayDay_7                     -0.043941   0.062793  -0.700 0.486964    
## DayDay_9                     -0.093202   0.058245  -1.600 0.115187    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -4.6580     0.1732  -26.89   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -495.27
## 
## $Bacteria_Bacteroidetes
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                  -1.45985    0.07056 -20.690  < 2e-16 ***
## Sample_TypeFeces              0.63296    0.06994   9.051 1.49e-12 ***
## Sample_TypeStomach Tube       0.03734    0.07467   0.500    0.619    
## Sample_TypeLiquid Strained    0.68808    0.06974   9.867 7.42e-14 ***
## Sample_TypeLiquid Unstrained  0.35169    0.08093   4.345 5.91e-05 ***
## Sample_TypeSolid              0.01534    0.07479   0.205    0.838    
## CowIDCow_2477                 0.09105    0.05875   1.550    0.127    
## CowIDCow_2549                 0.09216    0.05881   1.567    0.123    
## CowIDCow_796                  0.08511    0.05861   1.452    0.152    
## DayDay_7                     -0.01002    0.05289  -0.189    0.850    
## DayDay_9                      0.03951    0.04918   0.803    0.425    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  -5.2363     0.1756  -29.81   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -467.93

Next and collapse ASVs in the families and determine what families are differentially abundant.

This is a broad over view of the families that are significant differentially abundant in sample types. We will also dig down further and look at the genus and ASV level.

Phyla with Significant ASVs
Phylum #Significant ASVs Total ASVs Percent Significant ASVs
Actinobacteria 23 96 23.958333
Bacteroidetes 56 1257 4.455052
Chloroflexi 15 39 38.461539
Cyanobacteria 6 65 9.230769
Elusimicrobia 3 16 18.750000
Euryarchaeota 16 44 36.363636
Fibrobacteres 8 39 20.512821
Firmicutes 540 3095 17.447496
Kiritimatiellaeota 17 180 9.444444
Lentisphaerae 3 31 9.677419
Patescibacteria 3 14 21.428571
Proteobacteria 11 219 5.022831
Spirochaetes 8 138 5.797101
Tenericutes 15 188 7.978723
Verrucomicrobia 1 35 2.857143
Deferribacteres 0 1 0.000000
Epsilonbacteraeota 0 2 0.000000
Fusobacteria 0 4 0.000000
Gemmatimonadetes 0 1 0.000000
Planctomycetes 0 15 0.000000
Synergistetes 0 6 0.000000

There are 725 significantly differentially abundant ASVs with p < 0.05. Most of these ASVs were from the phyla Firmicutes and Bacteroidetes, but that is in part due to them being the dominant ASVs in the data set. As a percentage of ASVs, Chloroflexi and Euryarchaeota played a large role in distinguish different sample types.

We will graph out the significantly different ASVs from these phylums. First, we look at signficantly differentially abundant ASVs Chloroflexi and Euryarchaeota.

Here we can see that the Euryarchaeota that are important for telling samples types apart are all methanogens. Feces has a strong negative effect on most of these methanogens (methogens are lower in feces). Interestingly, fecal samples have lower Flexilinea.

In addition, based on the DPCoA without Bacteroidetes and Firmicutes we can see that Actinobacteria and Spirochaetes also play and important role in distinguishing liquid strained and fecal from grab samples respectively.

Next we examine the different ASVs in the phylum Bacteroidetes and Firmicutes.

This is a graph of the significant differentially abundant ASVs in the phylum Bacteroidetes.

This is a graph of the significant differentially abundant ASVs in the phylum Firmicutes.

Now we will look further up the phylogenetic tree and collapse ASVs into genera and look for genera differentially abundnant.

There are 121 significantly differentially abundant genera with p < 0.05 and 113 with a p < 0.01. After running corncob 158 genera could not be fit with the model, but 134 were fit to the model.

Let’s extract the ASVs and their p-values.

Differentially Abundant Taxa
p_value ASV Taxa
1 1.29e-03 ASV_1 Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group
2 1.29e-03 ASV_10 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans
3 1.29e-03 ASV_1006 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Candidatus_Soleaferrea
4 1.29e-03 ASV_1016 Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis
5 1.29e-03 ASV_103 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1
6 1.29e-03 ASV_105 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group
7 1.29e-03 ASV_1118 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_4
8 1.29e-03 ASV_1130 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018
9 1.29e-03 ASV_1132 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group
10 1.29e-03 ASV_1161 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006
11 1.29e-03 ASV_1169 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Syntrophococcus
12 1.29e-03 ASV_117 Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus
13 1.29e-03 ASV_120 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002
14 1.29e-03 ASV_1220 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_5
15 1.29e-03 ASV_1221 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium
16 1.29e-03 ASV_124 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group
18 1.29e-03 ASV_1366 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio
19 1.29e-03 ASV_1372 Bacteria_Fusobacteria_Fusobacteriia_Fusobacteriales_Fusobacteriaceae_Fusobacterium
20 1.29e-03 ASV_14 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium
21 1.29e-03 ASV_1403 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Howardella
22 1.29e-03 ASV_1434 Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae_Methanocorpusculum
23 1.29e-03 ASV_1440 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium
24 1.29e-03 ASV_145 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group
25 1.29e-03 ASV_149 Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio
27 1.29e-03 ASV_16 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group
28 1.29e-03 ASV_168 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Turicibacter
29 1.29e-03 ASV_1682 Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1
30 1.29e-03 ASV_169 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-004
31 1.29e-03 ASV_172 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809
32 1.29e-03 ASV_176 Bacteria_Proteobacteria_Gammaproteobacteria_Pseudomonadales_Pseudomonadaceae_Pseudomonas
33 1.29e-03 ASV_183 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014
34 1.29e-03 ASV_184 Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera
35 1.29e-03 ASV_1915 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_FD2005
36 1.29e-03 ASV_192 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group
37 1.29e-03 ASV_199 Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella
38 1.29e-03 ASV_2 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group
39 1.29e-03 ASV_20 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1
40 1.29e-03 ASV_201 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group
42 1.29e-03 ASV_2079 Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae_Campylobacter
43 1.29e-03 ASV_210 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10
44 1.29e-03 ASV_212 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010
48 1.29e-03 ASV_22 Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella
49 1.29e-03 ASV_2217 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae_Parabacteroides
50 1.29e-03 ASV_23 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1
53 1.29e-03 ASV_232 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1
54 1.29e-03 ASV_246 Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma
55 1.29e-03 ASV_247 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-009
56 1.29e-03 ASV_248 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group
57 1.29e-03 ASV_25 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio
58 1.29e-03 ASV_2540 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_Denitrobacterium
59 1.29e-03 ASV_26 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004
60 1.29e-03 ASV_267 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013
62 1.29e-03 ASV_29 Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_Treponema_2
63 1.29e-03 ASV_298 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax
65 1.29e-03 ASV_3 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005
66 1.29e-03 ASV_311 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella
67 1.29e-03 ASV_320 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10
68 1.29e-03 ASV_3270 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Caproiciproducens
69 1.29e-03 ASV_330 Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae_Akkermansia
70 1.29e-03 ASV_336 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_dgA-11_gut_group
72 1.29e-03 ASV_348 Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011
73 1.29e-03 ASV_357 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002
74 1.29e-03 ASV_36 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae_Bacteroides
76 1.29e-03 ASV_37 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter
77 1.29e-03 ASV_376 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group
78 1.29e-03 ASV_399 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_2
79 1.29e-03 ASV_4 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group
80 1.29e-03 ASV_409 Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea
81 1.29e-03 ASV_418 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium
82 1.29e-03 ASV_428 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia
83 1.29e-03 ASV_442 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Phascolarctobacterium
84 1.29e-03 ASV_450 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter
85 1.29e-03 ASV_457 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008
86 1.29e-03 ASV_462 Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium
87 1.29e-03 ASV_471 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium
88 1.29e-03 ASV_474 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001
89 1.29e-03 ASV_48 Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae_Romboutsia
90 1.29e-03 ASV_510 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Alloprevotella
93 1.29e-03 ASV_560 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6
94 1.29e-03 ASV_563 Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae_Candidatus_Endomicrobium
95 1.29e-03 ASV_57 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia
96 1.29e-03 ASV_60 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Alistipes
98 1.29e-03 ASV_622 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium
99 1.29e-03 ASV_636 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009
100 1.29e-03 ASV_656 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter
101 1.29e-03 ASV_66 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum
102 1.29e-03 ASV_670 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Roseburia
103 1.29e-03 ASV_674 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera
104 1.29e-03 ASV_68 Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter
105 1.29e-03 ASV_7 Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter
106 1.29e-03 ASV_71 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2
107 1.29e-03 ASV_72 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001
108 1.29e-03 ASV_733 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004
109 1.29e-03 ASV_757 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_1
110 1.29e-03 ASV_783 Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_p-1088-a5_gut_group
111 1.29e-03 ASV_8 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum
112 1.29e-03 ASV_819 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Flavonifractor
113 1.29e-03 ASV_83 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_9
114 1.29e-03 ASV_837 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Agathobacter
116 1.29e-03 ASV_90 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella
117 1.29e-03 ASV_902 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002
118 1.29e-03 ASV_91 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003
120 1.29e-03 ASV_953 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group
121 1.29e-03 ASV_963 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Anaerosporobacter
47 2.46e-03 ASV_2183 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_3
61 2.46e-03 ASV_2731 Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Fretibacterium
91 2.46e-03 ASV_520 Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Nocardiaceae_Rhodococcus
115 2.46e-03 ASV_887 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK4A136_group
119 2.46e-03 ASV_921 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-010
75 3.62e-03 ASV_3698 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelatoclostridium
97 3.62e-03 ASV_601 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009
17 5.99e-03 ASV_1258 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-006
52 9.51e-03 ASV_2319 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Fusicatenibacter
64 1.64e-02 ASV_2981 Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae_Planococcus
26 1.85e-02 ASV_1509 Bacteria_Firmicutes_Bacilli_Lactobacillales_Lactobacillaceae_Lactobacillus
71 1.85e-02 ASV_3393 Bacteria_Firmicutes_Bacilli_Bacillales_Staphylococcaceae_Staphylococcus
92 2.52e-02 ASV_534 Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae_Devosia
41 2.94e-02 ASV_2068 Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium_1
46 2.94e-02 ASV_2134 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_2
51 3.12e-02 ASV_2306 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-001
45 3.65e-02 ASV_2120 Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_CPla-4_termite_group

These are genera that are differentailly abundant between sample types and their false discovery corrected p-value. ASVs are listed by significance (p < 0.05).

We will now plot out all these taxa in comparison to grab samples.

##             x       xmin       xmax
## 1 -1.11267855 -1.8019687 -0.4233884
## 2  0.01801409 -0.5188173  0.5548455
## 3 -0.88724045 -1.5615566 -0.2129243
## 4 -0.06100509 -0.5700795  0.4480693
## 5 -0.80587250 -1.4864173 -0.1253277
## 6 -4.40965054 -5.4032656 -3.4160355
##                                           taxa
## 1 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 2 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 3 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 4 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 5 Lachnospiraceae_Lachnospiraceae_FE2018_group
## 6 Lachnospiraceae_Lachnospiraceae_ND3007_group
##                                     variable     Phylum
## 1             Feces\nDifferential\nAbundance Firmicutes
## 2      Stomach Tube\nDifferential\nAbundance Firmicutes
## 3   Liquid Strained\nDifferential\nAbundance Firmicutes
## 4             Solid\nDifferential\nAbundance Firmicutes
## 5 Liquid Unstrained\nDifferential\nAbundance Firmicutes
## 6             Feces\nDifferential\nAbundance Firmicutes

This is a graph of genera that are significantly differentially abundant across a sample type. The graph is of our model coefficent with a 95% confidence interval. Negative coefficients suggest that a taxon is differentially abundant across that sample type and that samples from that type are expected to have lower relative abundance. Conversely, postive coefficients suggest that a taxon is differentially abundant across that sample type and that samples from that type are expected to have higher relative abundance.

Let’s take a deeper dive into how these gnera separate by phyla.

## 
##     Actinobacteria      Bacteroidetes        Chloroflexi 
##                  7                 12                  1 
##      Elusimicrobia Epsilonbacteraeota      Euryarchaeota 
##                  2                  1                  3 
##      Fibrobacteres         Firmicutes       Fusobacteria 
##                  1                 80                  1 
##     Planctomycetes     Proteobacteria       Spirochaetes 
##                  2                  7                  1 
##      Synergistetes        Tenericutes    Verrucomicrobia 
##                  1                  1                  1

80 of the 121 significantly different taxa are Firmicutes. If we move the p-value to > 0.01 there are 75 significantly different taxa which are Firmicutes. We will graph out just these 80 taxa.

A majority of these genera in the phylum Firmicutes are in the families Ruminococcaceae and Lachnospiraceae.

This is the graph of the genera that are significantly differentially abundant in the phylum Bacteroidetes.

We can look more closely at one of these ASVs (ASV_622) that feces has a strong negative impact on.

##                                                                     ASV_622 
## "Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium"
## OTU Table:          [1 taxa and 68 samples]
##                      taxa are rows
##         282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_622  31  32  15  17  19  14  10   8  18  10  10  24  13  14  17  23
##         298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_622  35  14  18  17  15  20  26  34   4  23  25  30  35  19  15  18
##         360 361 362 363 365 366 367 368 369 370 371 372 373 374 375 376
## ASV_622  36  39  10   2  14   0   0   0   0   0   0   0   0   1   0   0
##         378 379 380 381 382 383 384 385 386 387 388 389 390 505 506 507
## ASV_622   0  31  29  37  46  16  35  18  34  48  22  43   6   8   7  11
##         508 509 510 511
## ASV_622   6  54  28  34

This is the feature table for ASV_622, it looks as those there is only one read for Lachnospiraceae Oribacterium in feces.

## 
## Call:
## bbdml(formula = ASV_622 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = ps_gen)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -5.57156    0.12016 -46.367
## Sample_TypeFeces             -5.55295    1.01064  -5.494
## Sample_TypeStomach Tube      -0.27180    0.12128  -2.241
## Sample_TypeLiquid Strained   -0.14208    0.11770  -1.207
## Sample_TypeLiquid Unstrained -0.27676    0.13396  -2.066
## Sample_TypeSolid             -0.03301    0.10920  -0.302
## CowIDCow_2477                 0.21587    0.10444   2.067
## CowIDCow_2549                 0.17021    0.10772   1.580
## CowIDCow_796                 -0.17494    0.11833  -1.478
## DayDay_7                     -0.06593    0.09719  -0.678
## DayDay_9                      0.04943    0.09005   0.549
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces                      0.000000994 ***
## Sample_TypeStomach Tube                    0.0290 *  
## Sample_TypeLiquid Strained                 0.2324    
## Sample_TypeLiquid Unstrained               0.0435 *  
## Sample_TypeSolid                           0.7636    
## CowIDCow_2477                              0.0434 *  
## CowIDCow_2549                              0.1197    
## CowIDCow_796                               0.1449    
## DayDay_7                                   0.5003    
## DayDay_9                                   0.5852    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -9.0948     0.4929  -18.45 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -181.86

Here we see the output of our hypothesis test. Feces is significantly different that other rumen samples. Additionally, both liquid straind and stomach tube samples have significantly lower abundance of this taxa when compared to grab samples. There is individual cow variation, but the day doesn’t make a significant difference.

Let’s graph out the abundance of Lachnospiraceae Oribacterium.

These graphs show that ASV_622 Lachnospiraceae Oribacterium is in lower abundance in fecal samples.

## 
## Call:
## bbdml(formula = ASV_20 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -1.69605    0.09946 -17.052
## Sample_TypeFeces             -0.43825    0.11515  -3.806
## Sample_TypeStomach Tube       0.20191    0.10317   1.957
## Sample_TypeLiquid Strained    1.33969    0.09448  14.180
## Sample_TypeLiquid Unstrained  0.77679    0.10850   7.159
## Sample_TypeSolid              0.03152    0.10552   0.299
## CowIDCow_2477                 0.12762    0.08214   1.554
## CowIDCow_2549                 0.11890    0.08238   1.443
## CowIDCow_796                  0.01186    0.08332   0.142
## DayDay_7                      0.00962    0.07586   0.127
## DayDay_9                      0.08982    0.06897   1.302
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces                         0.000352 ***
## Sample_TypeStomach Tube                  0.055336 .  
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained        0.00000000189 ***
## Sample_TypeSolid                         0.766242    
## CowIDCow_2477                            0.125893    
## CowIDCow_2549                            0.154474    
## CowIDCow_796                             0.887356    
## DayDay_7                                 0.899541    
## DayDay_9                                 0.198148    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -4.6695     0.1762   -26.5 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -434.14
## 
## Call:
## bbdml(formula = ASV_20 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams2)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -1.69605    0.09946 -17.052
## Sample_TypeFeces             -0.43825    0.11515  -3.806
## Sample_TypeStomach Tube       0.20191    0.10317   1.957
## Sample_TypeLiquid Strained    1.33969    0.09448  14.180
## Sample_TypeLiquid Unstrained  0.77679    0.10850   7.159
## Sample_TypeSolid              0.03152    0.10552   0.299
## CowIDCow_2477                 0.12762    0.08214   1.554
## CowIDCow_2549                 0.11890    0.08238   1.443
## CowIDCow_796                  0.01186    0.08332   0.142
## DayDay_7                      0.00962    0.07586   0.127
## DayDay_9                      0.08982    0.06897   1.302
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces                         0.000352 ***
## Sample_TypeStomach Tube                  0.055336 .  
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained        0.00000000189 ***
## Sample_TypeSolid                         0.766242    
## CowIDCow_2477                            0.125893    
## CowIDCow_2549                            0.154474    
## CowIDCow_796                             0.887356    
## DayDay_7                                 0.899541    
## DayDay_9                                 0.198148    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -4.6695     0.1762   -26.5 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -434.14

Hypothesis testing of relative abundance of Prevotellaceae.

## 
## Call:
## bbdml(formula = ASV_3 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -0.65855    0.04447 -14.809
## Sample_TypeFeces              1.76038    0.04717  37.323
## Sample_TypeStomach Tube       0.03498    0.04563   0.767
## Sample_TypeLiquid Strained   -0.22649    0.04665  -4.855
## Sample_TypeLiquid Unstrained  0.07624    0.05140   1.483
## Sample_TypeSolid              0.13751    0.04495   3.059
## CowIDCow_2477                 0.03856    0.03821   1.009
## CowIDCow_2549                -0.09324    0.03885  -2.400
## CowIDCow_796                  0.03687    0.03858   0.956
## DayDay_7                     -0.03020    0.03485  -0.867
## DayDay_9                     -0.04726    0.03254  -1.452
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces             < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.4465    
## Sample_TypeLiquid Strained                0.00001 ***
## Sample_TypeLiquid Unstrained               0.1436    
## Sample_TypeSolid                           0.0034 ** 
## CowIDCow_2477                              0.3172    
## CowIDCow_2549                              0.0197 *  
## CowIDCow_796                               0.3433    
## DayDay_7                                   0.3899    
## DayDay_9                                   0.1520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.0056     0.1917  -31.33 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -402.99
## 
## Call:
## bbdml(formula = ASV_3 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams2)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -0.65855    0.04447 -14.809
## Sample_TypeFeces              1.76038    0.04717  37.323
## Sample_TypeStomach Tube       0.03498    0.04563   0.767
## Sample_TypeLiquid Strained   -0.22649    0.04665  -4.855
## Sample_TypeLiquid Unstrained  0.07624    0.05140   1.483
## Sample_TypeSolid              0.13751    0.04495   3.059
## CowIDCow_2477                 0.03856    0.03821   1.009
## CowIDCow_2549                -0.09324    0.03885  -2.400
## CowIDCow_796                  0.03687    0.03858   0.956
## DayDay_7                     -0.03020    0.03485  -0.867
## DayDay_9                     -0.04726    0.03254  -1.452
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeFeces             < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.4465    
## Sample_TypeLiquid Strained                0.00001 ***
## Sample_TypeLiquid Unstrained               0.1436    
## Sample_TypeSolid                           0.0034 ** 
## CowIDCow_2477                              0.3172    
## CowIDCow_2549                              0.0197 *  
## CowIDCow_796                               0.3433    
## DayDay_7                                   0.3899    
## DayDay_9                                   0.1520    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.0056     0.1917  -31.33 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -402.99

Hypothesis testing of relative abundance of Ruminococcaceae.

## 
## Call:
## bbdml(formula = ASV_2 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value
## (Intercept)                   0.042374   0.064372   0.658
## Sample_TypeFeces             -1.810536   0.079047 -22.905
## Sample_TypeStomach Tube      -0.174821   0.064394  -2.715
## Sample_TypeLiquid Strained   -0.947437   0.068013 -13.930
## Sample_TypeLiquid Unstrained -0.649631   0.075585  -8.595
## Sample_TypeSolid             -0.139437   0.064160  -2.173
## CowIDCow_2477                -0.131409   0.057870  -2.271
## CowIDCow_2549                 0.004171   0.057745   0.072
## CowIDCow_796                 -0.040359   0.057518  -0.702
## DayDay_7                      0.014258   0.052239   0.273
## DayDay_9                     -0.029545   0.048922  -0.604
##                                          Pr(>|t|)    
## (Intercept)                                0.5131    
## Sample_TypeFeces             < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.0088 ** 
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained      0.0000000000082 ***
## Sample_TypeSolid                           0.0340 *  
## CowIDCow_2477                              0.0270 *  
## CowIDCow_2549                              0.9427    
## CowIDCow_796                               0.4858    
## DayDay_7                                   0.7859    
## DayDay_9                                   0.5483    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -5.1338     0.1794  -28.62 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -429.01
## 
## Call:
## bbdml(formula = ASV_2 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams2)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value
## (Intercept)                   0.042374   0.064372   0.658
## Sample_TypeFeces             -1.810536   0.079047 -22.905
## Sample_TypeStomach Tube      -0.174821   0.064394  -2.715
## Sample_TypeLiquid Strained   -0.947437   0.068013 -13.930
## Sample_TypeLiquid Unstrained -0.649631   0.075585  -8.595
## Sample_TypeSolid             -0.139437   0.064160  -2.173
## CowIDCow_2477                -0.131409   0.057870  -2.271
## CowIDCow_2549                 0.004171   0.057745   0.072
## CowIDCow_796                 -0.040359   0.057518  -0.702
## DayDay_7                      0.014258   0.052239   0.273
## DayDay_9                     -0.029545   0.048922  -0.604
##                                          Pr(>|t|)    
## (Intercept)                                0.5131    
## Sample_TypeFeces             < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.0088 ** 
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeLiquid Unstrained      0.0000000000082 ***
## Sample_TypeSolid                           0.0340 *  
## CowIDCow_2477                              0.0270 *  
## CowIDCow_2549                              0.9427    
## CowIDCow_796                               0.4858    
## DayDay_7                                   0.7859    
## DayDay_9                                   0.5483    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -5.1338     0.1794  -28.62 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -429.01

Hypothesis testing of relative abundance of Lachnospiraceae.

Alpha Diversity

Richness

Richness is defined as an estimate the number of ASVs in a sample. Next we will use breakaway to estimate the number of missing species based on the sequence depth and number of rare taxa in the data. These estimates account for different sequencing depths!

The error bars here are quite large, but this is to be expected as there is a lot of uncertainty in estimating alpha diversity.

Next we will test the hypothesis that different sample types have the same microbial diversity.

##                               Estimates Standard Errors p-values
## (Intercept)                  2021.81504        48.63103    0.000
## Sample_TypeGrab Sample       2097.41821       169.47911    0.000
## Sample_TypeLiquid Strained   2252.37940       185.14713    0.000
## Sample_TypeLiquid Unstrained 2267.87495       160.57081    0.000
## Sample_TypeStomach Tube      1590.78095       118.21733    0.000
## Sample_TypeSolid             1810.28830       123.71986    0.000
## CowIDCow_2477                  78.63928        84.39906    0.351
## CowIDCow_2549                 156.77270        99.34590    0.115
## CowIDCow_796                  -57.60818       106.37136    0.588
## DayDay_7                      -36.47393        88.72531    0.681
## DayDay_9                     -112.34992        77.42422    0.147
##                               Estimates Standard Errors p-values
## Sample_TypeFeces             2021.75358        73.87303    0.000
## Sample_TypeGrab Sample       4119.10429       169.47362    0.000
## Sample_TypeLiquid Strained   4274.33138       185.14037    0.000
## Sample_TypeLiquid Unstrained 4289.55899       160.56363    0.000
## Sample_TypeStomach Tube      3612.48064       118.20446    0.000
## Sample_TypeSolid             3832.13025       123.70992    0.000
## CowIDCow_2477                  78.70047        84.38617    0.351
## CowIDCow_2549                 156.85072        99.33510    0.114
## CowIDCow_796                  -57.62115       106.36304    0.588
## DayDay_7                      -36.52707        88.71495    0.681
## DayDay_9                     -112.31280        77.41588    0.147
##                                Estimates Standard Errors p-values
## (Intercept)                   4119.16582        48.63357    0.000
## Sample_TypeFeces             -2097.31618        73.89187    0.000
## Sample_TypeLiquid Strained     155.03662       185.15015    0.402
## Sample_TypeLiquid Unstrained   170.61198       160.57402    0.288
## Sample_TypeStomach Tube       -506.48308       118.22309    0.000
## Sample_TypeSolid              -286.99295       123.72430    0.020
## CowIDCow_2477                   78.61278        84.40483    0.352
## CowIDCow_2549                  156.79239        99.35073    0.115
## CowIDCow_796                   -57.70879       106.37509    0.587
## DayDay_7                       -36.47887        88.72994    0.681
## DayDay_9                      -112.31633        77.42795    0.147

When you break the rumen samples up into different sample types betta() estimates the mean species-level diversity are significantly different compared to fecal samples. Neither the cow or day caused a significant shift in species level diversity. When compared to the grab sample the stomach tube and solid samples have significatly less mean species-level diversity.

Evenness

Evenness is defined as how balanced the ASVs are; in other words do they exist in approximately the same relative abundance (1=very even). DivNet will estimate Shannon diversity in the presence of an ecological/microbial network! It also adjusts for different sequencing depths.

Here we will first look to see if samples types differ.

First, we will graph divnet’s estimation of shannon diversity.

Let’s look at hypothesis testing for DivNet estimates of shannon and diversity.

## [1] "hypothesis test for Shannon diversity"
## Hypothesis testing:
##   p-value for global test: 0
##                                Estimates Standard Errors p-values
## (Intercept)                   6.28626928     0.007833397    0.000
## Sample_TypeGrab Sample        0.42233374     0.019789481    0.000
## Sample_TypeLiquid Strained    0.33332816     0.016776556    0.000
## Sample_TypeLiquid Unstrained  0.45963678     0.024974179    0.000
## Sample_TypeSolid              0.40306231     0.014932992    0.000
## Sample_TypeStomach Tube       0.35163894     0.019836911    0.000
## CowIDCow_2477                -0.07519473     0.014980824    0.000
## CowIDCow_2549                -0.03249017     0.015576432    0.037
## CowIDCow_796                 -0.06513514     0.018650721    0.000
## DayDay_7                     -0.01866298     0.013726526    0.174
## DayDay_9                      0.04294924     0.014576081    0.003
## Hypothesis testing:
##   p-value for global test: 0
##                                 Estimates Standard Errors p-values
## (Intercept)                   6.736599905     0.007388884    0.000
## Sample_TypeFeces             -0.409523052     0.041617576    0.000
## Sample_TypeStomach Tube      -0.095140434     0.013441522    0.000
## Sample_TypeLiquid Strained   -0.090070120     0.017307448    0.000
## Sample_TypeSolid             -0.023506296     0.019564916    0.230
## Sample_TypeLiquid Unstrained  0.021480919     0.015079179    0.154
## CowIDCow_2477                -0.095425089     0.017819806    0.000
## CowIDCow_2549                -0.044188813     0.014767877    0.003
## CowIDCow_796                 -0.087036353     0.016435309    0.000
## DayDay_7                     -0.039248141     0.014234720    0.006
## DayDay_9                      0.007514973     0.012613441    0.551

Both the cow and day had a significant effect on evenness. Fecal samples had significantly lower evenness than samples from the rumen.

We will put a graph of the richness and evenness together as a figure for publication

Beta Diversity

We will plot the bray-curtis distances from Divnet. DivNet uses covariate information to share strength across samples and obtain an estimate about the beta diversity of the ecosystem not the samples.

Graph of estimates of bray-curtis distance from model with day and cowID

Graph of estimates of bray-curtis distance from model without day and cowID.

Grab vs fecal samples

We will remove other a few sample types to compress the data down and look just at the grab sample and feces.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 5164 taxa and 24 samples ]
## sample_data() Sample Data:       [ 24 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 5164 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 5164 tips and 5162 internal nodes ]

After subsetting the data we have 5164 ASVs in 24 samples.

Since we saw in the DPCoA that there were two populations of Firmicutes and Bacteriodests that separated rumen and fecal samples, we can ingestigate whether these are different genera or different species that make up this differences.

## [1] "Found in feces not in GS"
## [1] "Barnesiellaceae"       "Chitinophagaceae"      "p-2534-18B5_gut_group"
## [4] "GZKB124"               "Hymenobacteraceae"
## [1] "Found in GS not in feces"
##  [1] "Leuconostocaceae"       "Carnobacteriaceae"     
##  [3] "Aerococcaceae"          "Syntrophomonadaceae"   
##  [5] "Bacteroidetes_BD2-2"    "PeH15"                 
##  [7] "M2PB4-65_termite_group" "COB_P4-1_termite_group"
##  [9] "Spirosomaceae"          "Porphyromonadaceae"

These are the families that are found in one and not the other sample type.

## [1] "Found in feces not in GS"
##  [1] "Hungatella"                   "Coprococcus_3"               
##  [3] "Lachnospiraceae_NC2004_group" "Cellulosilyticum"            
##  [5] "Terrisporobacter"             "Clostridioides"              
##  [7] "Paeniclostridium"             "Ruminococcaceae_UCG-011"     
##  [9] "Breznakia"                    "Allobaculum"                 
## [11] "Dielma"                       "Jeotgalicoccus"              
## [13] "Lysinibacillus"               "Odoribacter"                 
## [15] "Sanguibacteroides"            "Taibaiella"                  
## [17] "Hymenobacter"                 "Harryflintia"                
## [19] "Negativibacillus"             "Fournierella"                
## [21] "Anaerofilum"                  "Pygmaiobacter"               
## [23] "Faecalibacterium"             "Intestinimonas"              
## [25] "Lachnoclostridium_5"
## [1] "Found in GS not in feces"
##  [1] "Acetatifactor"                "Lachnospiraceae_UCG-006"     
##  [3] "Shuttleworthia"               "Lachnoclostridium_1"         
##  [5] "Lachnoclostridium_12"         "Lachnospira"                 
##  [7] "Lachnospiraceae_NK4B4_group"  "GCA-900066575"               
##  [9] "Veillonellaceae_UCG-001"      "Quinella"                    
## [11] "Schwartzia"                   "Selenomonas_4"               
## [13] "Helcococcus"                  "Peptoniphilus"               
## [15] "Erysipelotrichaceae_UCG-008"  "Weissella"                   
## [17] "Desemzia"                     "Aerococcus"                  
## [19] "Pelospora"                    "Prevotellaceae_YAB2003_group"
## [21] "U29-B03"                      "Rikenella"                   
## [23] "Dyadobacter"                  "Tannerella"                  
## [25] "Porphyromonas"                "Angelakisella"               
## [27] "Ruminococcaceae_UCG-001"      "CAG-352"                     
## [29] "Ruminococcaceae_UCG-012"

These are the genera that are found in one and not the other sample type.

## [1] "Found in feces not in GS"
## [1] "sedimentorum" "ramosum"      "massiliensis"
## [1] "Found in GS not in feces"
##  [1] "intestinalis"  "xylanivorans"  "fibrisolvens"  "hungatei"     
##  [5] "succinivorans" "lipolyticus"   "ovis"          "indolicus"    
##  [9] "equigenerosi"  "incerta"       "ruminis"       "bryantii"     
## [13] "hamtensis"     "levii"

These are the species that are found in one and not the other sample type.

There are 1134 ASVs that are in feces, which are not in grab samples and there are 2102 ASVs in grab samples that are not in feces.

Corncob

We test all the taxa in our data to see if they are differentially-abundant or differentially-variable. The differentialTest function will these tests on all taxa, while controlling the false discovery rate to account for multiple comparisons.

Although there are species to species differences between samples we might expect this to be the normal variation in sample collection. Thus, we are most concerned with particular family or generna that might be excluded when sampling via different methods.

As we saw that when we graphed out relative abundance of families we will check to see if these differences are significant after taking into account library size differences. Then we will look lower taxonomically.

##                                            ASV_2 
##                     "Firmicutes_Lachnospiraceae" 
##                                          ASV_348 
##                   "Firmicutes_Defluviitaleaceae" 
##                                           ASV_23 
##                     "Firmicutes_Veillonellaceae" 
##                                           ASV_48 
##               "Firmicutes_Peptostreptococcaceae" 
##                                         ASV_1956 
##       "Firmicutes_Clostridiales_vadinBB60_group" 
##                                          ASV_246 
##                 "Tenericutes_Anaeroplasmataceae" 
##                                          ASV_117 
##                    "Firmicutes_Streptococcaceae" 
##                                         ASV_2071 
##                      "Firmicutes_Planococcaceae" 
##                                          ASV_384 
##                      "Firmicutes_Peptococcaceae" 
##                                         ASV_1682 
##                    "Firmicutes_Clostridiaceae_1" 
##                                          ASV_442 
##                  "Firmicutes_Acidaminococcaceae" 
##                                         ASV_1016 
##                      "Firmicutes_Eubacteriaceae" 
##                                          ASV_330 
##                "Verrucomicrobia_Akkermansiaceae" 
##                                         ASV_2079 
##          "Epsilonbacteraeota_Campylobacteraceae" 
##                                         ASV_1100 
##                "Elusimicrobia_Elusimicrobiaceae" 
##                                          ASV_783 
##                   "Planctomycetes_Pirellulaceae" 
##                                          ASV_563 
##                 "Elusimicrobia_Endomicrobiaceae" 
##                                          ASV_171 
##             "Proteobacteria_Succinivibrionaceae" 
##                                         ASV_1336 
##                "Proteobacteria_Burkholderiaceae" 
##                                         ASV_2314 
##                  "Proteobacteria_Oligoflexaceae" 
##                                            ASV_7 
##              "Euryarchaeota_Methanobacteriaceae" 
##                                          ASV_231 
##          "Euryarchaeota_Methanomethylophilaceae" 
##                                         ASV_1434 
##            "Euryarchaeota_Methanocorpusculaceae" 
##                                          ASV_534 
##                     "Proteobacteria_Devosiaceae" 
##                                           ASV_29 
##                   "Spirochaetes_Spirochaetaceae" 
##                                         ASV_1548 
##                   "Lentisphaerae_Victivallaceae" 
##                                         ASV_2068 
##              "Actinobacteria_Corynebacteriaceae" 
##                                          ASV_656 
## "Actinobacteria_Coriobacteriales_Incertae_Sedis" 
##                                          ASV_172 
##                 "Actinobacteria_Eggerthellaceae" 
##                                           ASV_90 
##                    "Actinobacteria_Atopobiaceae" 
##                                           ASV_68 
##                 "Fibrobacteres_Fibrobacteraceae" 
##                                          ASV_409 
##                    "Chloroflexi_Anaerolineaceae" 
##                                          ASV_499 
##                   "Synergistetes_Synergistaceae" 
##                                            ASV_1 
##                 "Firmicutes_Christensenellaceae" 
##                                           ASV_26 
##                   "Bacteroidetes_Prevotellaceae" 
##                                           ASV_36 
##                   "Bacteroidetes_Bacteroidaceae" 
##                                         ASV_2770 
##                   "Bacteroidetes_Marinifilaceae" 
##                                          ASV_995 
##                   "Bacteroidetes_Muribaculaceae" 
##                                         ASV_1084 
##                             "Bacteroidetes_F082" 
##                                          ASV_994 
##              "Bacteroidetes_Sphingobacteriaceae" 
##                                          ASV_197 
##     "Bacteroidetes_Bacteroidales_BS11_gut_group" 
##                                           ASV_60 
##                    "Bacteroidetes_Rikenellaceae" 
##                                          ASV_572 
##                "Bacteroidetes_Marinilabiliaceae" 
##                                          ASV_536 
##                         "Bacteroidetes_p-251-o5" 
##                                         ASV_2217 
##                   "Bacteroidetes_Tannerellaceae" 
##                                          ASV_822 
##                "Bacteroidetes_Paludibacteraceae" 
##                                          ASV_651 
##         "Bacteroidetes_Bacteroidales_RF16_group" 
##                                            ASV_3 
##                     "Firmicutes_Ruminococcaceae"

There are 48 families that are significantly different between fecal and grab samples.

These are the families that are significantly lower and higher in abundance.

## 
## -1  1 
## 30 18

There are 18 families significantly increased and 30 significantly decreased in relative abundance compared to grab samples.

x taxa Family
3 -5.5479763 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae (ASV_23) Veillonellaceae
41 -4.8958710 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidales_BS11_gut_group (ASV_197) Bacteroidales_BS11_gut_group
43 -4.8435765 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Marinilabiliaceae (ASV_572) Marinilabiliaceae
17 -4.4552940 Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae (ASV_563) Endomicrobiaceae
31 -4.4179317 Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae (ASV_68) Fibrobacteraceae
33 -4.4073698 Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae (ASV_499) Synergistaceae
18 -3.8406088 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae (ASV_171) Succinivibrionaceae
22 -3.8244025 Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae (ASV_231) Methanomethylophilaceae
6 -3.0967818 Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae (ASV_246) Anaeroplasmataceae
32 -2.9542980 Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae (ASV_409) Anaerolineaceae
24 -2.9465011 Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae (ASV_534) Devosiaceae
20 -2.3601932 Bacteria_Proteobacteria_Deltaproteobacteria_Oligoflexales_Oligoflexaceae (ASV_2314) Oligoflexaceae
44 -2.1251118 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_p-251-o5 (ASV_536) p-251-o5
28 -1.9605047 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis (ASV_656) Coriobacteriales_Incertae_Sedis
30 -1.8100719 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae (ASV_90) Atopobiaceae
40 -1.6584080 Bacteria_Bacteroidetes_Bacteroidia_Sphingobacteriales_Sphingobacteriaceae (ASV_994) Sphingobacteriaceae
39 -1.5196692 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_F082 (ASV_1084) F082
25 -1.5130522 Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae (ASV_29) Spirochaetaceae
21 -1.4923050 Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae (ASV_7) Methanobacteriaceae
1 -1.4413798 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae (ASV_2) Lachnospiraceae
27 -1.3854374 Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae (ASV_2068) Corynebacteriaceae
12 -1.1462353 Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae (ASV_1016) Eubacteriaceae
7 -1.1093855 Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae (ASV_117) Streptococcaceae
34 -1.0002190 Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae (ASV_1) Christensenellaceae
2 -0.9622930 Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae (ASV_348) Defluviitaleaceae
29 -0.9606860 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae (ASV_172) Eggerthellaceae
19 -0.8850722 Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae (ASV_1336) Burkholderiaceae
11 -0.6191481 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae (ASV_442) Acidaminococcaceae
38 -0.4438094 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Muribaculaceae (ASV_995) Muribaculaceae
35 -0.3491789 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae (ASV_26) Prevotellaceae
16 0.7348044 Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae (ASV_783) Pirellulaceae
42 0.8358951 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae (ASV_60) Rikenellaceae
37 0.9817063 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Marinifilaceae (ASV_2770) Marinifilaceae
9 1.0539220 Bacteria_Firmicutes_Clostridia_Clostridiales_Peptococcaceae (ASV_384) Peptococcaceae
47 1.1177019 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidales_RF16_group (ASV_651) Bacteroidales_RF16_group
48 1.1785720 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae (ASV_3) Ruminococcaceae
15 1.3666778 Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae (ASV_1100) Elusimicrobiaceae
10 1.6291444 Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1 (ASV_1682) Clostridiaceae_1
45 1.7352336 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae (ASV_2217) Tannerellaceae
5 2.2880851 Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_vadinBB60_group (ASV_1956) Clostridiales_vadinBB60_group
14 2.6322533 Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae (ASV_2079) Campylobacteraceae
26 3.0609734 Bacteria_Lentisphaerae_Lentisphaeria_Victivallales_Victivallaceae (ASV_1548) Victivallaceae
46 3.2160642 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Paludibacteraceae (ASV_822) Paludibacteraceae
8 3.3023998 Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae (ASV_2071) Planococcaceae
23 3.9963476 Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae (ASV_1434) Methanocorpusculaceae
4 4.5037536 Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae (ASV_48) Peptostreptococcaceae
13 4.6224111 Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae (ASV_330) Akkermansiaceae
36 5.3588153 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae (ASV_36) Bacteroidaceae
## [1] "Model for Peptostreptococcaceae"
## 
## Call:
## bbdml(formula = ASV_48 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value          Pr(>|t|)    
## (Intercept)       -6.9644     0.3372 -20.655 0.000000000000582 ***
## Sample_TypeFeces   4.3477     0.3223  13.491 0.000000000370577 ***
## CowIDCow_2477     -0.2735     0.1186  -2.305            0.0349 *  
## CowIDCow_2549     -0.1772     0.1215  -1.458            0.1641    
## CowIDCow_796       0.2097     0.1063   1.972            0.0661 .  
## DayDay_7           0.2602     0.1047   2.485            0.0244 *  
## DayDay_9           0.4111     0.1024   4.015            0.0010 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value        Pr(>|t|)    
## (Intercept)  -6.7448     0.4179  -16.14 0.0000000000254 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -83.154
## [1] "Model for Akkermansiaceae"
## 
## Call:
## bbdml(formula = ASV_330 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)      -8.27005    0.64229 -12.876 0.000000000737 ***
## Sample_TypeFeces  4.71006    0.61628   7.643 0.000000997988 ***
## CowIDCow_2477     0.30451    0.23539   1.294         0.2142    
## CowIDCow_2549     0.59090    0.23030   2.566         0.0207 *  
## CowIDCow_796      0.51348    0.22589   2.273         0.0372 *  
## DayDay_7          0.04634    0.18572   0.250         0.8061    
## DayDay_9         -0.08257    0.19196  -0.430         0.6728    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)   -6.061      0.451  -13.44 0.000000000392 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -68.472
## [1] "Model for Bacteroidaceae"
## 
## Call:
## bbdml(formula = ASV_36 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value          Pr(>|t|)    
## (Intercept)      -6.58850    0.27165 -24.254 0.000000000000048 ***
## Sample_TypeFeces  5.48235    0.26807  20.452 0.000000000000678 ***
## CowIDCow_2477    -0.22519    0.05542  -4.064          0.000903 ***
## CowIDCow_2549    -0.08155    0.05860  -1.392          0.183085    
## CowIDCow_796     -0.24183    0.05468  -4.423          0.000427 ***
## DayDay_7         -0.13691    0.04904  -2.792          0.013058 *  
## DayDay_9         -0.11920    0.04946  -2.410          0.028333 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)  -7.6553     0.5714   -13.4 0.000000000411 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -82.185
## [1] "Model for Veillonellaceae"
## 
## Call:
## bbdml(formula = ASV_23 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value             Pr(>|t|)    
## (Intercept)      -3.75237    0.11655 -32.195 0.000000000000000564 ***
## Sample_TypeFeces -5.62348    0.57920  -9.709 0.000000041362350627 ***
## CowIDCow_2477     0.33876    0.13059   2.594              0.01958 *  
## CowIDCow_2549     0.20408    0.13773   1.482              0.15782    
## CowIDCow_796      0.08529    0.13895   0.614              0.54797    
## DayDay_7         -0.38034    0.10482  -3.629              0.00226 ** 
## DayDay_9         -0.27460    0.11020  -2.492              0.02406 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -18.02     102.87  -0.175    0.863
## 
## 
## Log-likelihood: -45.747
## [1] "Model for Marinifilaceae"
## 
## Call:
## bbdml(formula = ASV_2770 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value          Pr(>|t|)    
## (Intercept)       -6.9769     0.3349 -20.834 0.000000000000509 ***
## Sample_TypeFeces   0.9070     0.2727   3.327           0.00427 ** 
## CowIDCow_2477     -0.7115     0.3571  -1.992           0.06369 .  
## CowIDCow_2549     -0.2403     0.3590  -0.669           0.51287    
## CowIDCow_796       0.4016     0.2624   1.531           0.14539    
## DayDay_7          -0.2217     0.2529  -0.877           0.39365    
## DayDay_9          -0.3895     0.2695  -1.445           0.16769    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value Pr(>|t|)
## (Intercept)   -18.02     116.78  -0.154    0.879
## 
## 
## Log-likelihood: -43.09
## [1] "Model for Bacteroidales_BS11_gut_group"
## 
## Call:
## bbdml(formula = ASV_197 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value           Pr(>|t|)    
## (Intercept)      -3.85845    0.15016 -25.696 0.0000000000000195 ***
## Sample_TypeFeces -4.77223    0.54227  -8.801 0.0000001575346194 ***
## CowIDCow_2477    -0.03706    0.16834  -0.220             0.8285    
## CowIDCow_2549    -0.34477    0.18772  -1.837             0.0849 .  
## CowIDCow_796     -0.02837    0.16832  -0.169             0.8682    
## DayDay_7         -0.26834    0.15820  -1.696             0.1092    
## DayDay_9          0.23722    0.14364   1.651             0.1181    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value     Pr(>|t|)    
## (Intercept)  -8.0549     0.8796  -9.157 0.0000000921 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -52.524
## [1] "Model for Fibrobacteraceae"
## 
## Call:
## bbdml(formula = ASV_29 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                   Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)      -2.647050   0.419377  -6.312 0.0000103 ***
## Sample_TypeFeces -1.669545   0.361365  -4.620  0.000284 ***
## CowIDCow_2477     0.003809   0.437963   0.009  0.993168    
## CowIDCow_2549     0.932873   0.414670   2.250  0.038898 *  
## CowIDCow_796     -0.121804   0.441738  -0.276  0.786278    
## DayDay_7          0.712349   0.360838   1.974  0.065887 .  
## DayDay_9         -0.148602   0.383329  -0.388  0.703375    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value    Pr(>|t|)    
## (Intercept)  -3.2789     0.3615  -9.071 0.000000105 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -134.17
## [1] "Model for Spirochaetaceae"
## 
## Call:
## bbdml(formula = ASV_68 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value           Pr(>|t|)    
## (Intercept)      -2.79001    0.11492 -24.279 0.0000000000000473 ***
## Sample_TypeFeces -4.49686    0.35791 -12.564 0.0000000010544203 ***
## CowIDCow_2477     0.31230    0.13279   2.352             0.0318 *  
## CowIDCow_2549     0.07762    0.14036   0.553             0.5879    
## CowIDCow_796      0.32862    0.13328   2.466             0.0254 *  
## DayDay_7         -0.05507    0.11132  -0.495             0.6275    
## DayDay_9         -0.01997    0.11247  -0.178             0.8613    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)  -6.8347     0.4993  -13.69 0.000000000299 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -78.079
## [1] "Model for Christensenellaceae"
## 
## Call:
## bbdml(formula = ASV_1 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value      Pr(>|t|)    
## (Intercept)       0.32931    0.16785   1.962        0.0674 .  
## Sample_TypeFeces -1.49195    0.13292 -11.224 0.00000000538 ***
## CowIDCow_2477     0.07971    0.18096   0.440        0.6655    
## CowIDCow_2549    -0.32060    0.18676  -1.717        0.1053    
## CowIDCow_796     -0.01653    0.17810  -0.093        0.9272    
## DayDay_7         -0.23819    0.15907  -1.497        0.1538    
## DayDay_9          0.02002    0.15683   0.128        0.9000    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)  -3.8665     0.2923  -13.23 0.000000000495 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -155.04
## [1] "Model for Rikenellaceae"
## 
## Call:
## bbdml(formula = ASV_60 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_fams)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value       Pr(>|t|)    
## (Intercept)      -1.15572    0.09990 -11.568 0.000000003491 ***
## Sample_TypeFeces  1.00619    0.07487  13.439 0.000000000392 ***
## CowIDCow_2477    -0.02057    0.10380  -0.198         0.8454    
## CowIDCow_2549    -0.19311    0.10515  -1.837         0.0849 .  
## CowIDCow_796      0.01051    0.10297   0.102         0.9200    
## DayDay_7         -0.07651    0.08972  -0.853         0.4064    
## DayDay_9         -0.01074    0.09039  -0.119         0.9069    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value        Pr(>|t|)    
## (Intercept)  -5.0415     0.3071  -16.41 0.0000000000197 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -141.9

We will look at a couple genera.

## [1] "Model for Fibrobacter"
## 
## Call:
## bbdml(formula = ASV_68 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_gen)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value    Pr(>|t|)    
## (Intercept)      -0.02493    0.28801  -0.087      0.9321    
## Sample_TypeFeces -2.73012    0.33675  -8.107 0.000000466 ***
## CowIDCow_2477     0.49871    0.32837   1.519      0.1483    
## CowIDCow_2549    -0.59569    0.33729  -1.766      0.0964 .  
## CowIDCow_796      0.38756    0.32444   1.195      0.2497    
## DayDay_7         -0.35679    0.28192  -1.266      0.2238    
## DayDay_9          0.18459    0.28904   0.639      0.5321    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value   Pr(>|t|)    
## (Intercept)  -3.1612     0.3596   -8.79 0.00000016 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -77.336
## [1] "Model for Treponema_2"
## 
## Call:
## bbdml(formula = ASV_29 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = sig_gen)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value    Pr(>|t|)    
## (Intercept)       0.02493    0.28801   0.087      0.9321    
## Sample_TypeFeces  2.73012    0.33675   8.107 0.000000466 ***
## CowIDCow_2477    -0.49871    0.32837  -1.519      0.1483    
## CowIDCow_2549     0.59569    0.33729   1.766      0.0964 .  
## CowIDCow_796     -0.38756    0.32444  -1.195      0.2497    
## DayDay_7          0.35679    0.28192   1.266      0.2238    
## DayDay_9         -0.18459    0.28904  -0.639      0.5321    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value   Pr(>|t|)    
## (Intercept)  -3.1612     0.3596   -8.79 0.00000016 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -77.336

These are graphs of the relative abundance of families significantly differently between fecal and grab samples. This is figure 6.

After running corncob 131 genera could not be fit with the model, but 130 were fit to the model and 114 were significanlty differentially abundant genera and 657significanlty differentially abundant ASVs.

We will look into taxa could not be fit to the model and see if we can determine why.

## [1] 131
## OTU Table:          [131 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_4633   0   0   0   0   0   0   0   0   0   0   0   0   2   0   0   2
## ASV_429    2   2   3   2   4   2  12  13   5   5   6   6   0   0   0   0
## ASV_5279   0   0   0   0   0   0   0   0   0   0   0   3   0   0   0   0
## ASV_669    3   7   2   6   7   8  12   8   3   6   4   2   0   0   0   0
## ASV_713    0   0   0   0   0   0   0   0   0   0   0   0  28  20  27  22
## ASV_4679   0   0   0   0   1   1   0   0   2   0   0   1   0   0   0   0
## ASV_878    6   5   4   0   0   3   0   0   0   4   6   2   0   0   0   0
## ASV_4288   0   2   0   1   1   0   1   2   0   0   0   1   0   0   0   0
## ASV_793   15   7   7  12  16  15  14  14   9  17  13  19   0   0   0   0
## ASV_4973   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2583   1   2   1   1   1   0   2   1   0   5   0   4   0   0   0   0
## ASV_5230   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1393   0   0   0   0   0   0   0   0   0   0   0   0   7  19  14   5
## ASV_2417   0   0   1   0   0   0   0   0   0   1   0   1   0   0   0   0
## ASV_456   10   0   4   7   3   7   5   7   6   2   1   3   0   0   0   0
## ASV_4284   1   1   0   3   4   3   4   1   4   4   1   1   0   0   0   0
## ASV_2244   1   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_5146   0   1   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_2322   0   0   0   0   0   0   0   0   0   0   0   0   1   2   0   1
## ASV_113    0   0   0   0   0   0   0   0   0   0   0   0  33  31  32  47
## ASV_147    0   0   0   0   0   0   0   0   0   0   0   0  11  33  10  30
## ASV_4383   0   0   0   1   2   1   0   0   0   0   1   0   0   0   0   0
## ASV_4854   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5567   0   0   0   1   2   0   0   0   0   0   0   0   0   0   0   0
## ASV_5123   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5418   0   0   0   0   0   0   0   0   0   0   0   0   1   0   1   1
## ASV_4130   0   0   0   0   0   1   2   1   4   1   1   1   0   0   0   0
## ASV_1759   1   1   4   0   0   0   3   3   2   1   0   0   0   0   0   0
## ASV_413    0   1   1   0   0   1   0   0   0   0   0   1   0   0   0   0
## ASV_1612   0   0   0   0   1   1   0   0   0   0   0   1   0   0   0   1
## ASV_4673   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_3469   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3393   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_5204   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2981   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4744   0   0   0   0   0   0   0   0   0   0   0   0   0   0   2   0
## ASV_4508   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_3129   0   1   2   2   1   1   0   0   0   0   0   0   0   0   0   0
## ASV_5524   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_4013   0   0   0   0   1   0   0   2   1   2   0   0   0   0   0   0
## ASV_574    1   1   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1728   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_276    2   1   1   1   0   1   0   0   0   1   0   0   0   0   0   0
## ASV_511    3   4   3   1   1   0   5   7   4   2   2   3   0   0   0   0
## ASV_1518   1   0   2   0   0   2   0   2   0   2   2   0   0   0   0   0
## ASV_171   30  18  14   8   9  10   6  13   8   4   6   6   0   0   0   0
## ASV_1373   0   0   2   0   0   0   0   0   2   0   0   0   0   0   0   0
## ASV_1078   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4258   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1336   0   0   0   0   0   0   0   0   0   0   0   0   4   6   5   6
## ASV_5356   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   4
## ASV_2174   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2658   0   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_4109   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_1947   0   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_503    0   1   1   1   0   0   0   0   1   1   0   0   0   0   0   0
## ASV_424    3   0   1   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_2419   0   0   1   2   1   1   0   0   0   0   0   0   0   0   0   0
## ASV_2915   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4015   1   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4126   0   0   0   0   2   0   0   0   0   0   0   0   0   0   0   0
## ASV_3435   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2130   0   0   0   0   0   0   0   1   0   1   1   1   0   0   0   0
## ASV_4324   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4076   0   0   0   0   0   0   0   0   0   0   0   0   7   2   3   5
## ASV_5222   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_4211   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3936   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3276   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_5262   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_221    1   0   2   0   1   1   2   2   0   0   0   0   0   0   0   0
## ASV_2401   0   1   0   0   1   0   0   0   0   0   0   0   0   0   1   0
## ASV_4992   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1856   0   0   0   0   0   1   0   0   1   0   0   0   0   0   0   1
## ASV_3262   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5025   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_2037   0   0   0   0   1   0   0   0   3   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_5555   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3123   1   0   0   0   0   1   0   0   0   0   0   0   0   0   1   1
## ASV_2044   0   1   2   0   1   0   0   0   0   1   0   1   0   0   0   0
## ASV_4913   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1389   2   1   0   3   4   6   3   5   4   1   1   1   0   0   0   0
## ASV_3684   0   0   0   0   0   0   0   0   0   0   0   0   1   4   1   1
## ASV_901    2   0   1   1   4   1   1   0   5   0   2   1   0   0   0   0
## ASV_578    2   4   6   6   5   0   3   4   4   2   2   3   0   0   0   0
## ASV_5600   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   2
## ASV_4378   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1247   0   0   0   0   0   0   0   0   0   0   0   0  10   5  17   5
## ASV_3201   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_1042   0   1   0   0   0   0   0   0   0   0   1   1   0   0   0   1
## ASV_2594   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1307   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0
## ASV_2550   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1306   0   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_3273   0   0   1   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_520    1   0   2   0   0   0   2   0   1   0   0   0   0   0   0   1
## ASV_3119   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_5589   0   1   0   0   1   0   1   0   0   1   0   0   0   0   0   0
## ASV_2687   0   0   0   0   0   0   0   0   0   0   0   0   2   6   2   2
## ASV_4612   0   0   0   1   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_5602   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_499    3   7   2   9   3   3   2   3   2   4   5   0   0   0   0   0
## ASV_2617   1   0   0   0   0   0   1   1   0   1   2   0   0   0   0   0
## ASV_2770   0   0   0   0   0   0   0   0   0   0   0   0   2   3   3   3
## ASV_5521   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_1658   3   4   1   2   0   3   3   1   0   3   2   3   0   0   0   0
## ASV_1213   1   1   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_994    0   0   1   0   2   0   0   1   0   0   0   0   0   0   0   0
## ASV_5192   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_5568   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_2880   0   0   0   0   0   0   0   1   0   0   1   0   0   0   0   0
## ASV_3146   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_5036   0   0   0   0   0   0   1   0   0   2   0   0   0   0   0   0
## ASV_4270   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_4849   0   1   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2544   0   0   0   0   0   0   0   0   0   0   0   0   3   3   3   6
## ASV_1565   0   0   1   7   1   0   2   3   1   3   1   3   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0   0   0   0   0   9   8   2   7
## ASV_1756   0   0   0   0   0   0   0   0   0   0   0   0   2   4   2   1
## ASV_4771   0   0   1   0   0   0   1   0   0   0   0   1   0   0   0   0
## ASV_5492   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2759   0   0   0   0   0   0   0   0   0   0   0   0   3   2   3   4
## ASV_4822   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   2
## ASV_5006   0   0   0   0   0   0   0   0   0   0   0   0   1   1   0   1
## ASV_2171   2   0   2   7   1   0   2   1   2   0   1   1   0   0   0   0
## ASV_3188   0   0   0   1   0   0   1   0   1   1   0   0   0   0   0   0
## ASV_2318   1   2   3   1   2   7   1   1   1   0   5   4   0   0   0   0
## ASV_4340   0   0   0   0   0   0   0   0   0   0   0   0   0   1   1   1
## ASV_5426   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##          370 371 372 373 374 375 376 378
## ASV_4633   3   1   6   1   1   0   0   0
## ASV_429    0   0   0   0   0   0   0   0
## ASV_5279   2   0   3   0   2   0   1   1
## ASV_669    0   0   0   0   0   0   0   0
## ASV_713   26  35  64  46  48  20  23  15
## ASV_4679   0   0   0   0   0   0   0   0
## ASV_878    0   0   0   0   0   0   0   0
## ASV_4288   0   0   0   0   0   0   0   0
## ASV_793    0   0   0   0   0   0   0   0
## ASV_4973   0   0   0   0   0   0   0   0
## ASV_2583   0   0   0   0   0   0   0   0
## ASV_5230   0   0   0   0   0   1   0   0
## ASV_1393   4  14  26   7   7   5   7   2
## ASV_2417   0   0   0   0   0   0   1   0
## ASV_456    0   0   0   0   0   0   0   0
## ASV_4284   0   0   0   0   0   0   0   0
## ASV_2244   0   0   0   0   0   0   0   0
## ASV_5146   0   0   0   0   0   0   0   0
## ASV_2322   4   3   4   4   6   8   2   7
## ASV_113   69  55 101  85  70  61  78  53
## ASV_147   35  31  74  84  52  64  93  54
## ASV_4383   1   0   0   0   0   0   0   0
## ASV_4854   0   0   0   0   0   0   0   0
## ASV_5567   0   0   0   0   0   0   0   0
## ASV_5123   1   0   2   1   1   1   0   3
## ASV_5340   0   0   1   0   0   0   0   0
## ASV_5418   1   2   0   0   0   1   0   0
## ASV_4130   0   0   0   0   0   0   0   0
## ASV_1759   0   0   0   0   0   0   0   0
## ASV_413    0   0   0   0   0   0   0   0
## ASV_1612   0   0   1   0   1   0   2   0
## ASV_4673   0   0   0   0   0   0   0   0
## ASV_3469   0   0   0   0   0   0   0   0
## ASV_3393   0   0   1   0   0   0   0   0
## ASV_5204   0   0   1   0   0   0   0   0
## ASV_2981   0   0   0   0   1   0   0   0
## ASV_4744   2   2   1   0   1   1   5   1
## ASV_4508   0   0   4   0   1   0   0   0
## ASV_3129   0   0   0   0   0   0   0   0
## ASV_5524   0   0   0   0   3   1   0   0
## ASV_4013   0   1   1   0   1   0   0   0
## ASV_574    0   0   0   0   0   0   0   0
## ASV_1728   0   0   0   0   0   1   0   0
## ASV_276    0   0   0   0   0   1   0   0
## ASV_511    0   0   0   0   0   0   0   0
## ASV_1518   0   0   0   0   0   0   0   0
## ASV_171    0   0   0   0   0   0   0   0
## ASV_1373   0   0   0   0   0   0   0   0
## ASV_1078   0   0   0   0   0   0   0   0
## ASV_4258   0   0   0   0   0   0   0   1
## ASV_1336   5   6   6   6  16   9  13   5
## ASV_5356   0   0   0   0   0   2   1   1
## ASV_2174   0   0   0   0   0   0   0   0
## ASV_2658   0   0   0   0   0   0   0   0
## ASV_4109   0   0   0   0   0   0   0   0
## ASV_1947   0   0   0   0   0   0   0   0
## ASV_503    0   0   0   0   0   0   0   0
## ASV_424    0   0   0   0   0   0   0   0
## ASV_2419   0   0   0   0   0   0   0   0
## ASV_2915   0   0   0   0   0   0   0   0
## ASV_4015   0   0   0   0   0   0   0   1
## ASV_4126   0   0   0   0   0   0   0   0
## ASV_3435   0   0   0   0   0   0   0   0
## ASV_2130   0   0   0   0   0   0   0   0
## ASV_4324   6   2   0   0   1   2   2   3
## ASV_4076   2   5   4   4   1   2   1   0
## ASV_5222   0   0   0   0   0   0   0   0
## ASV_4211   0   1   0   0   1   0   0   1
## ASV_3936   0   0   0   0   0   0   0   0
## ASV_3276   0   0   0   0   0   0   0   0
## ASV_5262   0   0   0   0   0   0   0   0
## ASV_221    0   0   0   0   0   0   0   0
## ASV_2401   0   0   0   0   0   0   0   0
## ASV_4992   0   0   0   0   0   0   0   0
## ASV_1856   1   0   0   1   0   0   0   0
## ASV_3262   0   0   0   0   0   0   0   0
## ASV_5025   0   0   0   0   1   0   0   0
## ASV_2037   0   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0
## ASV_5555   0   0   0   1   0   0   0   0
## ASV_3123   0   0   0   0   0   0   0   0
## ASV_2044   0   0   0   0   0   0   0   0
## ASV_4913   1   0   0   0   3   2   1   0
## ASV_1389   0   0   0   0   0   0   0   0
## ASV_3684   3   1   3   5   3   2   1   1
## ASV_901    0   0   0   0   0   0   0   0
## ASV_578    0   0   0   0   0   0   0   0
## ASV_5600   0   0   0   0   0   0   0   0
## ASV_4378   0   1   0   0   0   0   0   0
## ASV_1247   6   6  16   7  16   9  16  11
## ASV_3201   0   0   0   0   0   0   0   0
## ASV_1042   0   0   0   0   0   0   0   0
## ASV_2594   0   0   0   0   0   0   0   0
## ASV_1307   0   0   0   0   0   0   0   0
## ASV_2550   0   0   0   0   0   0   0   1
## ASV_1306   0   1   0   0   0   0   0   0
## ASV_3273   0   0   0   0   0   0   0   0
## ASV_520    0   0   1   0   0   0   0   0
## ASV_3119   0   0   0   0   0   0   0   0
## ASV_5589   0   0   0   0   0   0   0   0
## ASV_2687   3   5   2   6   1   1   1   2
## ASV_4612   0   0   0   0   0   0   0   0
## ASV_5602   2   0   0   0   0   0   0   0
## ASV_499    0   0   0   0   0   0   0   0
## ASV_2617   0   0   0   0   0   0   0   0
## ASV_2770   2   3  10   9  12  10   2   6
## ASV_5521   0   0   1   1   1   1   0   0
## ASV_1658   0   0   0   0   0   0   0   0
## ASV_1213   1   0   0   0   0   0   0   0
## ASV_994    1   0   0   0   0   0   0   0
## ASV_5192   0   0   0   0   0   0   0   0
## ASV_5568   0   0   0   0   0   0   0   0
## ASV_2880   0   0   0   0   0   0   0   0
## ASV_3146   0   0   0   0   0   0   0   0
## ASV_5036   0   0   0   0   0   0   0   0
## ASV_4270   0   0   0   0   0   0   0   0
## ASV_4849   0   0   1   0   0   2   3   0
## ASV_2544   4   5  17  15   7   9  12   9
## ASV_1565   0   0   0   0   0   0   0   0
## ASV_1448  11   7   9   5   5   6   7   4
## ASV_1756   4   2  17   8   5   5   8   8
## ASV_4771   0   0   1   0   0   0   0   0
## ASV_5492   0   0   0   1   2   1   1   0
## ASV_2759   8   5   5   4   1   5   7   7
## ASV_4822   1   0   2   2   0   1   3   1
## ASV_5006   2   1   2   2   1   1   2   2
## ASV_2171   0   0   0   0   0   0   0   0
## ASV_3188   0   0   0   0   0   0   0   0
## ASV_2318   0   0   0   0   0   0   0   0
## ASV_4340   1   3   4   0   0   1   2   2
## ASV_5426   1   2   0   1   2   0   0   1

Although, 131 taxa could not be fit with the model this looks to be due to circumstances where there is very few reads for a particular ASV (thus, a model can’t be fit) or instances where there is only reads in one sample type. See the feature table above.

## [1] 42
## [1] 67

There are 109 ASVs that have no reads in one sample type which is why they aren’t being fit to the model. Another 49 ASVs only have one read per sample type which will not allow them to be fit to the model.

## [1] "In feces, but not in grab samples"
##                                              ASV_713 
##           "Firmicutes_Lachnospiraceae_Coprococcus_3" 
##                                             ASV_1393 
##        "Firmicutes_Lachnospiraceae_Cellulosilyticum" 
##                                              ASV_113 
##    "Firmicutes_Peptostreptococcaceae_Clostridioides" 
##                                              ASV_147 
##  "Firmicutes_Peptostreptococcaceae_Paeniclostridium" 
##                                             ASV_1336 
##     "Proteobacteria_Burkholderiaceae_Parasutterella" 
##                                             ASV_1247 
##    "Actinobacteria_Bifidobacteriaceae_Aeriscardovia" 
##                                             ASV_2770 
##           "Bacteroidetes_Marinifilaceae_Odoribacter" 
##                                             ASV_2544 
## "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-011" 
##                                             ASV_1448 
##            "Firmicutes_Ruminococcaceae_Harryflintia" 
##                                             ASV_1756 
##        "Firmicutes_Ruminococcaceae_Negativibacillus" 
##                                             ASV_2759 
##           "Firmicutes_Ruminococcaceae_Pygmaiobacter"
## OTU Table:          [1 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1393   0   0   0   0   0   0   0   0   0   0   0   0   7  19  14   5
##          370 371 372 373 374 375 376 378
## ASV_1393   4  14  26   7   7   5   7   2
## OTU Table:          [1 taxa and 24 samples]
##                      taxa are rows
##         293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_113   0   0   0   0   0   0   0   0   0   0   0   0  33  31  32  47
##         370 371 372 373 374 375 376 378
## ASV_113  69  55 101  85  70  61  78  53
## OTU Table:          [1 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1448   0   0   0   0   0   0   0   0   0   0   0   0   9   8   2   7
##          370 371 372 373 374 375 376 378
## ASV_1448  11   7   9   5   5   6   7   4
## [1] "In grab samples, but not in feces"
##                                              ASV_429 
##           "Firmicutes_Lachnospiraceae_Acetatifactor" 
##                                              ASV_669 
##          "Firmicutes_Lachnospiraceae_Shuttleworthia" 
##                                              ASV_793 
## "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-006" 
##                                              ASV_456 
## "Firmicutes_Veillonellaceae_Veillonellaceae_UCG-001" 
##                                              ASV_171 
##   "Proteobacteria_Succinivibrionaceae_Succinivibrio"

These ASVs couldn’t be fit to the model since there was zero reads in one sample type, but the other sample type has over 50 reads.

Let’s graph the one with the most reads ASV_113 Clostridioides.

Now, we will return to the corncob output. We can see a list of differentially-abundant taxa using:

There are 114 genera differentially abundant. We will look at the unique families they represent.

# of significant genera in each family
Var1 Freq
Firmicutes_Lachnospiraceae 180
Firmicutes_Ruminococcaceae 156
Firmicutes_Christensenellaceae 105
Firmicutes_Family_XIII 30
Bacteroidetes_Rikenellaceae 24
Bacteroidetes_Prevotellaceae 19
Euryarchaeota_Methanobacteriaceae 13
Firmicutes_Erysipelotrichaceae 12
Chloroflexi_Anaerolineaceae 10
Spirochaetes_Spirochaetaceae 10
Actinobacteria_Atopobiaceae 9
Tenericutes 9
Kiritimatiellaeota 8
Actinobacteria_Eggerthellaceae 7
Bacteroidetes_F082 6
Fibrobacteres_Fibrobacteraceae 6
Bacteroidetes_Bacteroidales_BS11_gut_group 3
Firmicutes 3
Firmicutes_Defluviitaleaceae 3
Firmicutes_Peptococcaceae 3
Bacteroidetes 2
Bacteroidetes_Bacteroidaceae 2
Bacteroidetes_p-251-o5 2
Firmicutes_Acidaminococcaceae 2
Firmicutes_Clostridiaceae_1 2
Firmicutes_Eubacteriaceae 2
Firmicutes_Peptostreptococcaceae 2
Patescibacteria 2
Planctomycetes_Pirellulaceae 2
Proteobacteria 2
Proteobacteria_Desulfovibrionaceae 2
Proteobacteria_Succinivibrionaceae 2
Verrucomicrobia_Akkermansiaceae 2
Actinobacteria_Coriobacteriales_Incertae_Sedis 1
Bacteroidetes_Bacteroidales_RF16_group 1
Bacteroidetes_Marinilabiliaceae 1
Bacteroidetes_Muribaculaceae 1
Bacteroidetes_Tannerellaceae 1
Cyanobacteria 1
Elusimicrobia_Elusimicrobiaceae 1
Elusimicrobia_Endomicrobiaceae 1
Firmicutes_Lactobacillaceae 1
Firmicutes_Planococcaceae 1
Firmicutes_Streptococcaceae 1
Firmicutes_Veillonellaceae 1
Proteobacteria_Burkholderiaceae 1
Proteobacteria_Oligoflexaceae 1
Verrucomicrobia 1

This graphs the ASVs in Bacteroidetes differentially abundantant. We do see that Rikenellaceae is lower in abundandance in feces compared grab samples, but we saw this was familiy was higher in relative abundance before so we will double check that.

Statistiscs for Abundance of Akkermansiaceae
Sample_Type Genus mean sd sem
56 Feces Clostridioides 0.6387915 0.1383558 0.0399399
181 Feces Paeniclostridium 0.4938325 0.2294837 0.0662462
235 Feces Ruminococcaceae_UCG-005 0.2536037 0.7033963 0.0251856
76 Feces Dorea 0.2388953 0.1933942 0.0394764
30 Feces Bacteroides 0.2255830 0.2802845 0.0145321
223 Feces Romboutsia 0.1954684 0.3827171 0.0390609
281 Feces Tyzzerella 0.1555427 0.1656968 0.0276161
192 Feces Phascolarctobacterium 0.1503569 0.0986420 0.0201352
204 Feces Prevotellaceae_UCG-004 0.1315314 0.3258646 0.0192018
280 Feces Turicibacter 0.1190462 0.1990139 0.0287252
13 Feces Alistipes 0.1151407 0.1833281 0.0085851
73 Feces dgA-11_gut_group 0.0938341 0.1050319 0.0071465
11 Feces Agathobacter 0.0848349 0.0697738 0.0116290
185 Feces Parasutterella 0.0813552 0.0391629 0.0113053
109 Feces Harryflintia 0.0789645 0.0457608 0.0132100
154 Feces Mailhella 0.0741483 0.1563596 0.0170602
237 Feces Ruminococcaceae_UCG-009 0.0662564 0.0988824 0.0076289
12 Feces Akkermansia 0.0600574 0.0750389 0.0046183
7 Feces Aeriscardovia 0.0600208 0.0601411 0.0122762
169 Feces Negativibacillus 0.0573690 0.0345288 0.0099676
116 Feces Incertae_Sedis 0.0542774 0.0704945 0.0117491
23 Feces Anaerosporobacter 0.0530864 0.0533739 0.0077039
94 Feces Flavonifractor 0.0528531 0.0427194 0.0037182
283 Feces Tyzzerella_4 0.0467089 0.0498705 0.0058773
15 Feces Alloprevotella 0.0453476 0.0862643 0.0071887
61 Feces Coprococcus_3 0.0437105 0.0564572 0.0057621
103 Feces GCA-900066225 0.0408701 0.0328104 0.0066974
126 Feces Lachnoclostridium 0.0407673 0.0495309 0.0101105
241 Feces Ruminococcaceae_UCG-013 0.0395571 0.0572627 0.0018036
277 Feces Terrisporobacter 0.0369988 0.0248179 0.0071643
44 Feces Candidatus_Soleaferrea 0.0360129 0.0477317 0.0068895
222 Feces Rikenellaceae_RC9_gut_group 0.0356341 0.0859706 0.0015986
160 Feces Methanocorpusculum 0.0342023 0.0511104 0.0104329
186 Feces Parvibacter 0.0335902 0.0291808 0.0084238
227 Feces Ruminiclostridium_5 0.0317005 0.0429588 0.0050627
178 Feces Oscillibacter 0.0315691 0.0324547 0.0024190
89 Feces Family_XIII_AD3011_group 0.0305030 0.0680737 0.0032306
234 Feces Ruminococcaceae_UCG-004 0.0304327 0.0652095 0.0084185
48 Feces Cellulosilyticum 0.0297891 0.0569408 0.0082187
233 Feces Ruminococcaceae_UCG-002 0.0291055 0.0567230 0.0038595
239 Feces Ruminococcaceae_UCG-011 0.0263409 0.0228147 0.0038025
290 Feces XBB1006 0.0253367 0.0440793 0.0063623
108 Feces GWE2-31-10 0.0251856 0.0191693 0.0055337
238 Feces Ruminococcaceae_UCG-010 0.0248479 0.0461817 0.0008570
214 Feces Pygmaiobacter 0.0245344 0.0192048 0.0039202
184 Feces Parabacteroides 0.0241291 0.0298835 0.0060999
159 Feces Methanobrevibacter 0.0236423 0.0618265 0.0037215
226 Feces Ruminiclostridium_1 0.0214905 0.0556286 0.0060696
225 Feces Ruminiclostridium 0.0208239 0.0310066 0.0036542
285 Feces UBA1819 0.0193558 0.0156928 0.0045301
163 Feces Mogibacterium 0.0193521 0.0581515 0.0040714
114 Feces Hydrogenoanaerobacterium 0.0193362 0.0197852 0.0025543
174 Feces Odoribacter 0.0192082 0.0235864 0.0039311
67 Feces Denitrobacterium 0.0191882 0.0238792 0.0048743
3 Feces Acetobacter 0.0185080 0.0204518 0.0041747
40 Feces Campylobacter 0.0182729 0.0266641 0.0054428
57 Feces Clostridium_sensu_stricto_1 0.0164786 0.0278606 0.0030398
180 Feces p-1088-a5_gut_group 0.0155396 0.0417214 0.0034768
229 Feces Ruminiclostridium_9 0.0150709 0.0267372 0.0023272
53 Feces Christensenellaceae_R-7_group 0.0148646 0.0487342 0.0006503
203 Feces Prevotellaceae_UCG-003 0.0145027 0.0566721 0.0015390
231 Feces Ruminococcaceae_NK4A214_group 0.0141766 0.0460014 0.0014076
113 Feces Hungatella 0.0139791 0.0172950 0.0049926
10 Feces Aestuariispira 0.0139554 0.0196823 0.0056818
117 Feces Intestinimonas 0.0139085 0.0113642 0.0032806
133 Feces Lachnospiraceae_FCS020_group 0.0138013 0.0401638 0.0032157
91 Feces FD2005 0.0135530 0.0265794 0.0038364
145 Feces Lachnospiraceae_UCG-010 0.0134737 0.0161588 0.0023323
151 Feces Lysinibacillus 0.0134573 0.0148229 0.0042790
138 Feces Lachnospiraceae_NK4A136_group 0.0107925 0.0262609 0.0015474
88 Feces Faecalibacterium 0.0107498 0.0093950 0.0027121
79 Feces Elusimicrobium 0.0107198 0.0256244 0.0024657
87 Feces Eubacterium 0.0103994 0.0101764 0.0029377
137 Feces Lachnospiraceae_NK3A20_group 0.0103956 0.0594491 0.0019816
293 Feces NA 0.0103741 0.0392643 0.0002675
236 Feces Ruminococcaceae_UCG-007 0.0102813 0.0163617 0.0033398
45 Feces Caproiciproducens 0.0102036 0.0142604 0.0023767
81 Feces Erysipelatoclostridium 0.0101135 0.0147305 0.0024551
144 Feces Lachnospiraceae_UCG-009 0.0094588 0.0177503 0.0025620
224 Feces Roseburia 0.0091183 0.0161287 0.0014723
59 Feces Coprococcus_1 0.0083048 0.0124823 0.0018017
2 Feces Acetitomaculum 0.0082661 0.0252547 0.0010634
242 Feces Ruminococcaceae_UCG-014 0.0078948 0.0214008 0.0005786
60 Feces Coprococcus_2 0.0078869 0.0143832 0.0023972
217 Feces Raoultibacter 0.0074416 0.0086101 0.0024855
90 Feces Family_XIII_UCG-001 0.0073221 0.0186402 0.0020338
36 Feces Breznakia 0.0072076 0.0091047 0.0026283
96 Feces Fournierella 0.0071908 0.0085943 0.0017543
74 Feces Dielma 0.0071292 0.0083068 0.0023980
155 Feces Marvinbryantia 0.0070862 0.0185011 0.0007962
86 Feces Escherichia/Shigella 0.0069791 0.0095785 0.0027651
66 Feces Defluviitaleaceae_UCG-011 0.0069274 0.0173898 0.0015875
245 Feces Ruminococcus_2 0.0065609 0.0318101 0.0015748
176 Feces Olsenella 0.0065356 0.0136794 0.0013163
37 Feces Butyrivibrio 0.0063574 0.0117246 0.0023933
33 Feces Bilophila 0.0061762 0.0106983 0.0030883
130 Feces Lachnoclostridium_5 0.0060615 0.0084681 0.0024445
202 Feces Prevotellaceae_UCG-001 0.0060065 0.0271684 0.0010575
171 Feces Nitrosomonas 0.0059248 0.0102792 0.0029674
134 Feces Lachnospiraceae_FE2018_group 0.0057836 0.0098037 0.0020012
25 Feces Anaerovorax 0.0052314 0.0215634 0.0012706
50 Feces Cerasicoccus 0.0048723 0.0101461 0.0029289
249 Feces Sanguibacteroides 0.0048190 0.0065736 0.0018976
111 Feces hoa5-07d05_gut_group 0.0048156 0.0097705 0.0028205
128 Feces Lachnoclostridium_10 0.0047588 0.0159617 0.0013893
200 Feces Prevotellaceae_Ga6A1_group 0.0046212 0.0121785 0.0020297
75 Feces DNF00809 0.0045312 0.0099781 0.0006441
20 Feces Anaerofilum 0.0042118 0.0070094 0.0020234
265 Feces Streptococcus 0.0041349 0.0127466 0.0012265
161 Feces Methanosphaera 0.0040941 0.0093743 0.0012102
34 Feces Blautia 0.0038997 0.0121645 0.0007168
80 Feces Enterococcus 0.0038507 0.0063274 0.0018265
255 Feces Sellimonas 0.0036649 0.0079158 0.0016158
250 Feces Sarcina 0.0036622 0.0097637 0.0028185
194 Feces Pirellula 0.0036374 0.0069816 0.0020154
183 Feces Papillibacter 0.0034728 0.0115269 0.0008893
282 Feces Tyzzerella_3 0.0034292 0.0128156 0.0011699
228 Feces Ruminiclostridium_6 0.0033738 0.0091114 0.0007593
147 Feces Lactobacillus 0.0032990 0.0089522 0.0008614
83 Feces Erysipelotrichaceae_UCG-006 0.0032477 0.0074219 0.0015150
27 Feces Atopobium 0.0027888 0.0079088 0.0006884
262 Feces Sporobacter 0.0026935 0.0051575 0.0014888
21 Feces Anaerofustis 0.0026664 0.0049651 0.0007167
64 Feces CPla-4_termite_group 0.0025267 0.0074154 0.0015137
279 Feces Treponema_2 0.0024822 0.0156970 0.0004102
46 Feces Catenisphaera 0.0023699 0.0043432 0.0012538
246 Feces Saccharofermentans 0.0023208 0.0114662 0.0006620
173 Feces Ochrobactrum 0.0022955 0.0042134 0.0012163
85 Feces Erysipelotrichaceae_UCG-009 0.0021437 0.0081140 0.0010475
244 Feces Ruminococcus_1 0.0021079 0.0089509 0.0002786
230 Feces Ruminobacter 0.0019248 0.0062992 0.0010499
166 Feces Mucispirillum 0.0018388 0.0063697 0.0018388
258 Feces Solobacterium 0.0017884 0.0053905 0.0004921
170 Feces Neorhizobium 0.0017712 0.0040531 0.0008273
141 Feces Lachnospiraceae_UCG-002 0.0017172 0.0054352 0.0004529
28 Feces Aurantimonas 0.0015597 0.0037038 0.0010692
99 Feces Fusicatenibacter 0.0015533 0.0053807 0.0015533
143 Feces Lachnospiraceae_UCG-008 0.0014649 0.0055222 0.0002657
100 Feces Fusobacterium 0.0013048 0.0035323 0.0007210
292 Feces Z20 0.0012979 0.0044961 0.0012979
172 Feces Novosphingobium 0.0012785 0.0044289 0.0012785
275 Feces Taibaiella 0.0012785 0.0044289 0.0012785
43 Feces Candidatus_Saccharimonas 0.0012466 0.0033976 0.0006935
112 Feces Howardella 0.0012201 0.0049514 0.0006392
274 Feces Syntrophococcus 0.0010753 0.0036596 0.0002728
271 Feces Sutterella 0.0010377 0.0037369 0.0006228
195 Feces Planococcus 0.0009107 0.0031549 0.0009107
32 Feces Bifidobacterium 0.0008945 0.0030987 0.0008945
248 Feces Sanguibacter 0.0008945 0.0030987 0.0008945
135 Feces Lachnospiraceae_NC2004_group 0.0008615 0.0029843 0.0008615
95 Feces Flexilinea 0.0008526 0.0036413 0.0001683
132 Feces Lachnospiraceae_AC2044_group 0.0008081 0.0035506 0.0002237
5 Feces Actinobacillus 0.0008044 0.0027864 0.0008044
17 Feces Alysiella 0.0008044 0.0027864 0.0008044
125 Feces Kocuria 0.0008044 0.0027864 0.0008044
157 Feces Megasphaera 0.0008016 0.0027768 0.0008016
63 Feces Corynebacterium_1 0.0007743 0.0026185 0.0003779
198 Feces possible_genus_Sk018 0.0007410 0.0029886 0.0002876
52 Feces Chelatococcus 0.0007272 0.0025190 0.0007272
14 Feces Allobaculum 0.0006879 0.0023828 0.0006879
120 Feces Jeotgalicoccus 0.0006879 0.0023828 0.0006879
263 Feces Staphylococcus 0.0006879 0.0023828 0.0006879
266 Feces Subdoligranulum 0.0006879 0.0023828 0.0006879
220 Feces Rhodococcus 0.0006684 0.0022656 0.0004625
210 Feces Pseudochrobactrum 0.0006490 0.0022481 0.0006490
211 Feces Pseudoclavibacter 0.0006490 0.0022481 0.0006490
162 Feces Methylobacterium 0.0006425 0.0028343 0.0004724
92 Feces Fibrobacter 0.0004776 0.0035062 0.0001664
167 Feces Murdochiella 0.0004597 0.0022520 0.0004597
82 Feces Erysipelotrichaceae_UCG-004 0.0004415 0.0029695 0.0001470
264 Feces Stenotrophomonas 0.0004308 0.0021102 0.0004308
209 Feces Pseudobutyrivibrio 0.0003630 0.0019076 0.0002081
22 Feces Anaeroplasma 0.0003595 0.0025951 0.0001266
259 Feces Sphingobacterium 0.0003065 0.0018388 0.0003065
140 Feces Lachnospiraceae_UCG-001 0.0002982 0.0017890 0.0002982
70 Feces Desulfovibrio 0.0002802 0.0019098 0.0001473
243 Feces Ruminococcaceae_V9D2013_group 0.0002605 0.0016139 0.0001292
165 Feces Moryella 0.0002534 0.0019733 0.0001899
72 Feces Devosia 0.0002293 0.0013757 0.0002293
97 Feces Fretibacterium 0.0002293 0.0013757 0.0002293
146 Feces Lachnospiraceae_XPB1014_group 0.0002248 0.0015558 0.0000864
115 Feces Hymenobacter 0.0002163 0.0012979 0.0002163
253 Feces Selenomonas_1 0.0002131 0.0018081 0.0002131
24 Feces Anaerovibrio 0.0001839 0.0014243 0.0001839
188 Feces Pedobacter 0.0001839 0.0014243 0.0001839
136 Feces Lachnospiraceae_ND3007_group 0.0001800 0.0016394 0.0000946
270 Feces Succinivibrionaceae_UCG-002 0.0001723 0.0013346 0.0001723
41 Feces Candidatus_Endomicrobium 0.0001518 0.0012880 0.0001518
201 Feces Prevotellaceae_NK3B31_group 0.0000944 0.0009800 0.0000667
206 Feces probable_genus_10 0.0000913 0.0011837 0.0000913
38 Feces Butyrivibrio_2 0.0000912 0.0010955 0.0000482
212 Feces Pseudomonas 0.0000862 0.0009437 0.0000862
267 Feces Succiniclasticum 0.0000813 0.0009343 0.0000813
177 Feces Oribacterium 0.0000536 0.0007652 0.0000536
199 Feces Prevotella_1 0.0000325 0.0006350 0.0000104
1 Feces Acetatifactor 0.0000000 0.0000000 0.0000000
4 Feces Acinetobacter 0.0000000 0.0000000 0.0000000
6 Feces Aeribacillus 0.0000000 0.0000000 0.0000000
8 Feces Aerococcus 0.0000000 0.0000000 0.0000000
9 Feces Aeromicrobium 0.0000000 0.0000000 0.0000000
16 Feces Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium 0.0000000 0.0000000 0.0000000
18 Feces Anaerobiospirillum 0.0000000 0.0000000 0.0000000
19 Feces Anaerocella 0.0000000 0.0000000 0.0000000
26 Feces Angelakisella 0.0000000 0.0000000 0.0000000
29 Feces Aureimonas 0.0000000 0.0000000 0.0000000
31 Feces Bibersteinia 0.0000000 0.0000000 0.0000000
35 Feces Brevundimonas 0.0000000 0.0000000 0.0000000
39 Feces CAG-352 0.0000000 0.0000000 0.0000000
42 Feces Candidatus_Methanomethylophilus 0.0000000 0.0000000 0.0000000
47 Feces Caviibacter 0.0000000 0.0000000 0.0000000
49 Feces Cellvibrio 0.0000000 0.0000000 0.0000000
51 Feces Chelativorans 0.0000000 0.0000000 0.0000000
54 Feces Chryseobacterium 0.0000000 0.0000000 0.0000000
55 Feces Clavibacter 0.0000000 0.0000000 0.0000000
58 Feces Comamonas 0.0000000 0.0000000 0.0000000
62 Feces Corynebacterium 0.0000000 0.0000000 0.0000000
65 Feces Curtobacterium 0.0000000 0.0000000 0.0000000
68 Feces Desemzia 0.0000000 0.0000000 0.0000000
69 Feces Desulfobulbus 0.0000000 0.0000000 0.0000000
71 Feces Desulfuromonas 0.0000000 0.0000000 0.0000000
77 Feces Duganella 0.0000000 0.0000000 0.0000000
78 Feces Dyadobacter 0.0000000 0.0000000 0.0000000
84 Feces Erysipelotrichaceae_UCG-008 0.0000000 0.0000000 0.0000000
93 Feces Filifactor 0.0000000 0.0000000 0.0000000
98 Feces Frigoribacterium 0.0000000 0.0000000 0.0000000
101 Feces Galbitalea 0.0000000 0.0000000 0.0000000
102 Feces Gallicola 0.0000000 0.0000000 0.0000000
104 Feces GCA-900066575 0.0000000 0.0000000 0.0000000
105 Feces Gillisia 0.0000000 0.0000000 0.0000000
106 Feces Gilvimarinus 0.0000000 0.0000000 0.0000000
107 Feces Glutamicibacter 0.0000000 0.0000000 0.0000000
110 Feces Helcococcus 0.0000000 0.0000000 0.0000000
118 Feces Janthinobacterium 0.0000000 0.0000000 0.0000000
119 Feces Jeotgalibaca 0.0000000 0.0000000 0.0000000
121 Feces Kandleria 0.0000000 0.0000000 0.0000000
122 Feces Ketogulonicigenium 0.0000000 0.0000000 0.0000000
123 Feces Kineococcus 0.0000000 0.0000000 0.0000000
124 Feces Klebsiella 0.0000000 0.0000000 0.0000000
127 Feces Lachnoclostridium_1 0.0000000 0.0000000 0.0000000
129 Feces Lachnoclostridium_12 0.0000000 0.0000000 0.0000000
131 Feces Lachnospira 0.0000000 0.0000000 0.0000000
139 Feces Lachnospiraceae_NK4B4_group 0.0000000 0.0000000 0.0000000
142 Feces Lachnospiraceae_UCG-006 0.0000000 0.0000000 0.0000000
148 Feces Leptotrichia 0.0000000 0.0000000 0.0000000
149 Feces Leucobacter 0.0000000 0.0000000 0.0000000
150 Feces Limnohabitans 0.0000000 0.0000000 0.0000000
152 Feces M2PT2-76_termite_group 0.0000000 0.0000000 0.0000000
153 Feces Macellibacteroides 0.0000000 0.0000000 0.0000000
156 Feces Massilia 0.0000000 0.0000000 0.0000000
158 Feces Methanimicrococcus 0.0000000 0.0000000 0.0000000
164 Feces Moraxella 0.0000000 0.0000000 0.0000000
168 Feces Mycoplasma 0.0000000 0.0000000 0.0000000
175 Feces Oligella 0.0000000 0.0000000 0.0000000
179 Feces Oscillospira 0.0000000 0.0000000 0.0000000
182 Feces Pantoea 0.0000000 0.0000000 0.0000000
187 Feces Parvimonas 0.0000000 0.0000000 0.0000000
189 Feces Pelospora 0.0000000 0.0000000 0.0000000
190 Feces Peptococcus 0.0000000 0.0000000 0.0000000
191 Feces Peptoniphilus 0.0000000 0.0000000 0.0000000
193 Feces Pigmentiphaga 0.0000000 0.0000000 0.0000000
196 Feces Pontibacter 0.0000000 0.0000000 0.0000000
197 Feces Porphyromonas 0.0000000 0.0000000 0.0000000
205 Feces Prevotellaceae_YAB2003_group 0.0000000 0.0000000 0.0000000
207 Feces Proteiniclasticum 0.0000000 0.0000000 0.0000000
208 Feces Proteiniphilum 0.0000000 0.0000000 0.0000000
213 Feces Psychrobacter 0.0000000 0.0000000 0.0000000
215 Feces Pyramidobacter 0.0000000 0.0000000 0.0000000
216 Feces Quinella 0.0000000 0.0000000 0.0000000
218 Feces Rathayibacter 0.0000000 0.0000000 0.0000000
219 Feces Rhodobacter 0.0000000 0.0000000 0.0000000
221 Feces Rikenella 0.0000000 0.0000000 0.0000000
232 Feces Ruminococcaceae_UCG-001 0.0000000 0.0000000 0.0000000
240 Feces Ruminococcaceae_UCG-012 0.0000000 0.0000000 0.0000000
247 Feces Salana 0.0000000 0.0000000 0.0000000
251 Feces Schwartzia 0.0000000 0.0000000 0.0000000
252 Feces Sediminispirochaeta 0.0000000 0.0000000 0.0000000
254 Feces Selenomonas_4 0.0000000 0.0000000 0.0000000
256 Feces Shuttleworthia 0.0000000 0.0000000 0.0000000
257 Feces Slackia 0.0000000 0.0000000 0.0000000
260 Feces Sphingobium 0.0000000 0.0000000 0.0000000
261 Feces Sphingomonas 0.0000000 0.0000000 0.0000000
268 Feces Succinimonas 0.0000000 0.0000000 0.0000000
269 Feces Succinivibrio 0.0000000 0.0000000 0.0000000
272 Feces Suttonella 0.0000000 0.0000000 0.0000000
273 Feces Synergistes 0.0000000 0.0000000 0.0000000
276 Feces Tannerella 0.0000000 0.0000000 0.0000000
278 Feces Thermomonas 0.0000000 0.0000000 0.0000000
284 Feces U29-B03 0.0000000 0.0000000 0.0000000
286 Feces Variovorax 0.0000000 0.0000000 0.0000000
287 Feces Veillonellaceae_UCG-001 0.0000000 0.0000000 0.0000000
288 Feces Verticia 0.0000000 0.0000000 0.0000000
289 Feces Weissella 0.0000000 0.0000000 0.0000000
291 Feces Xylophilus 0.0000000 0.0000000 0.0000000
Statistiscs for Abundance of Rikenellaceae
Sample_Type Genus mean sd sem
9 Feces Alistipes 0.1151407 0.1833281 0.0085851
11 Feces dgA-11_gut_group 0.0938341 0.1050319 0.0071465
14 Feces Rikenellaceae_RC9_gut_group 0.0356341 0.0859706 0.0015986
16 Feces NA 0.0321720 0.0516502 0.0066680
38 Solid Rikenellaceae_RC9_gut_group 0.0305544 0.0893249 0.0016610
6 Grab Sample Rikenellaceae_RC9_gut_group 0.0293962 0.0865592 0.0016096
22 Stomach Tube Rikenellaceae_RC9_gut_group 0.0287573 0.0782038 0.0014542
46 Liquid Unstrained Rikenellaceae_RC9_gut_group 0.0240750 0.0592204 0.0013487
39 Solid U29-B03 0.0202607 0.0140115 0.0028601
30 Liquid Strained Rikenellaceae_RC9_gut_group 0.0195953 0.0571284 0.0010623
7 Grab Sample U29-B03 0.0176858 0.0225679 0.0046067
23 Stomach Tube U29-B03 0.0087306 0.0104589 0.0021349
47 Liquid Unstrained U29-B03 0.0079824 0.0112709 0.0028177
12 Feces hoa5-07d05_gut_group 0.0048156 0.0097705 0.0028205
44 Liquid Unstrained hoa5-07d05_gut_group 0.0040984 0.0076867 0.0027177
31 Liquid Strained U29-B03 0.0040380 0.0078627 0.0016050
4 Grab Sample hoa5-07d05_gut_group 0.0032071 0.0077284 0.0022310
32 Liquid Strained NA 0.0017208 0.0065606 0.0008470
28 Liquid Strained hoa5-07d05_gut_group 0.0015568 0.0042730 0.0012335
40 Solid NA 0.0015567 0.0064352 0.0008308
48 Liquid Unstrained NA 0.0015525 0.0054636 0.0008639
5 Grab Sample Rikenella 0.0014625 0.0050663 0.0014625
42 Liquid Unstrained Anaerocella 0.0012392 0.0035050 0.0012392
24 Stomach Tube NA 0.0012366 0.0054721 0.0007064
20 Stomach Tube hoa5-07d05_gut_group 0.0012348 0.0042773 0.0012348
45 Liquid Unstrained Rikenella 0.0009321 0.0026365 0.0009321
26 Liquid Strained Anaerocella 0.0007805 0.0027037 0.0007805
8 Grab Sample NA 0.0007000 0.0038342 0.0004950
37 Solid Rikenella 0.0006256 0.0021671 0.0006256
41 Liquid Unstrained Alistipes 0.0003632 0.0023145 0.0001327
43 Liquid Unstrained dgA-11_gut_group 0.0002380 0.0017008 0.0001417
17 Stomach Tube Alistipes 0.0002040 0.0018299 0.0000857
25 Liquid Strained Alistipes 0.0001770 0.0011256 0.0000527
1 Grab Sample Alistipes 0.0001556 0.0016626 0.0000779
35 Solid dgA-11_gut_group 0.0001345 0.0011416 0.0000777
27 Liquid Strained dgA-11_gut_group 0.0001136 0.0010386 0.0000707
33 Solid Alistipes 0.0000872 0.0009282 0.0000435
3 Grab Sample dgA-11_gut_group 0.0000813 0.0011941 0.0000813
19 Stomach Tube dgA-11_gut_group 0.0000686 0.0010082 0.0000686
2 Grab Sample Anaerocella 0.0000000 0.0000000 0.0000000
10 Feces Anaerocella 0.0000000 0.0000000 0.0000000
13 Feces Rikenella 0.0000000 0.0000000 0.0000000
15 Feces U29-B03 0.0000000 0.0000000 0.0000000
18 Stomach Tube Anaerocella 0.0000000 0.0000000 0.0000000
21 Stomach Tube Rikenella 0.0000000 0.0000000 0.0000000
29 Liquid Strained Rikenella 0.0000000 0.0000000 0.0000000
34 Solid Anaerocella 0.0000000 0.0000000 0.0000000
36 Solid hoa5-07d05_gut_group 0.0000000 0.0000000 0.0000000

From these graphs we can see that Rikenellaceae_RC9_gut_group appears to be higher in feces there is also other genera (Alistipes,dgA_11_gut_group) in the Rikenellaceae family that cause the overall relative abundance of this family to be higher than in grab samples. However, there are certain ASVs in Rikenellaceae that are significantly lower in feces. This backs up the corncob data.

Genera in Firmicutes differentially abundantant between feces and grab samples.

# of Significant ASVs by Phyla
Var1 Freq
Firmicutes 504
Bacteroidetes 62
Actinobacteria 17
Euryarchaeota 13
Chloroflexi 10
Spirochaetes 10
Tenericutes 9
Kiritimatiellaeota 8
Proteobacteria 8
Fibrobacteres 6
Verrucomicrobia 3
Elusimicrobia 2
Patescibacteria 2
Planctomycetes 2
Cyanobacteria 1

While the most common phyla to have significant differentially abundant taxa were Firmicutes and Bacteroidetes this could be because they are the most dominant taxa rather than really being “more important” in distinguishing sample types.

# of Significant ASVs by Phyla
Phylum #Significant ASVs Total ASVs Percent Significant ASVs
Actinobacteria 17 96 17.708333
Bacteroidetes 62 1257 4.932379
Chloroflexi 10 39 25.641026
Cyanobacteria 1 65 1.538461
Elusimicrobia 2 16 12.500000
Euryarchaeota 13 44 29.545455
Fibrobacteres 6 39 15.384615
Firmicutes 504 3095 16.284330
Kiritimatiellaeota 8 180 4.444444
Patescibacteria 2 14 14.285714
Planctomycetes 2 15 13.333333
Proteobacteria 8 219 3.652968
Spirochaetes 10 138 7.246377
Tenericutes 9 188 4.787234
Verrucomicrobia 3 35 8.571429
Deferribacteres 0 1 0.000000
Epsilonbacteraeota 0 2 0.000000
Fusobacteria 0 4 0.000000
Gemmatimonadetes 0 1 0.000000
Lentisphaerae 0 31 0.000000
Synergistetes 0 6 0.000000

This table shows that while Firmicutes and Bacteroidetes are the most common phyla to have differentially abundant taxa this is in part due the fact that they are the most prevelant phyla. As a percent Chloroflexi and Euryarcheota are more common.

We will graph out the significantly different taxa from these phylums.

Here we can see that the Euryarchaeota that are important for telling samples types apart are all methogens. Feces has a strong negative effect on most of these methanogens (methogens are lower in feces). Interestingly, fecal samples have lower Flexilinea.

## [1] "Flexilinea"
## OTU Table:          [38 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_3963   0   1   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1206   2   0   2   1   1   6   0   0   0   0   0   2   0   0   0   0
## ASV_1519   0   1   0   3   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_1003   2   1   1   2   2   1   2   2   1   1   2   2   0   0   0   0
## ASV_3326   0   0   1   0   1   0   1   0   0   0   1   0   0   0   0   0
## ASV_1572   0   0   3   2   2   3   2   0   3   0   0   0   0   0   0   0
## ASV_1315   1   0   1   1   1   3   1   1   2   0   0   0   0   0   1   0
## ASV_3266   0   2   1   0   2   1   0   0   0   0   1   0   0   0   0   0
## ASV_727    2   0   3   2   0   4   4   1   1   3   2   4   0   1   0   0
## ASV_2479   0   0   0   0   3   0   0   1   1   0   0   2   0   1   0   0
## ASV_1570   1   0   0   1   2   1   0   0   2   0   2   0   0   0   0   1
## ASV_1257   0   0   0   1   1   0   1   0   2   0   0   0   0   0   0   0
## ASV_1826   1   1   0   2   0   2   0   1   0   0   1   0   0   0   0   0
## ASV_4222   0   2   0   1   0   0   0   0   0   1   0   0   0   0   0   0
## ASV_612    1   1   1   3   1   3   0   1   2   0   2   1   0   0   0   1
## ASV_2625   1   0   0   0   0   0   1   1   1   2   0   0   0   0   0   0
## ASV_3203   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_2739   3   0   0   0   0   0   0   0   0   0   2   1   0   0   0   0
## ASV_3861   0   0   0   1   0   0   1   2   1   0   0   0   0   0   0   0
## ASV_3258   0   0   0   6   2   1   0   0   0   0   0   0   0   0   0   0
## ASV_2612   0   2   0   4   0   0   0   0   0   1   1   0   0   0   0   0
## ASV_1761   0   0   1   2   0   1   0   0   1   0   1   1   0   0   0   0
## ASV_2122   0   1   0   2   1   1   0   1   1   0   1   1   0   0   0   0
## ASV_1879   0   0   0   1   2   0   2   3   1   0   5   0   0   0   0   0
## ASV_2100   0   2   2   1   0   1   1   1   0   1   1   0   0   0   1   0
## ASV_409    6   4   4   8   3   7   8   2   5   3   3   2   0   0   0   0
## ASV_4093   0   1   0   0   0   1   0   1   1   0   0   0   0   0   0   0
## ASV_2353   0   0   0   1   0   0   1   0   1   1   0   4   0   0   0   0
## ASV_594    2   1   2   3   1   2   6   3   3   6   6   7   2   0   1   0
## ASV_2831   0   1   0   0   0   0   0   1   0   0   2   1   0   0   0   0
## ASV_743    2   0   1   2   0   1   6   5   6   1   2   2   0   0   0   0
## ASV_1877   0   1   0   0   0   1   1   1   1   0   1   0   0   0   0   0
## ASV_1428   2   3   0   0   1   1   2   4   0   0   0   0   0   1   0   0
## ASV_1620   1   1   1   2   1   2   1   2   0   1   1   1   0   0   0   0
## ASV_4680   0   0   0   0   0   1   0   0   0   0   1   0   0   0   0   0
## ASV_2984   3   0   1   1   1   0   0   0   0   0   0   1   0   0   0   0
## ASV_3303   0   2   0   1   1   0   0   0   0   0   2   1   0   0   0   0
## ASV_3402   0   0   0   2   1   1   0   0   0   1   2   0   0   0   0   0
##          370 371 372 373 374 375 376 378
## ASV_3963   0   0   0   0   1   0   0   0
## ASV_1206   0   2   0   0   0   0   0   0
## ASV_1519   0   1   0   0   0   0   1   0
## ASV_1003   0   0   1   0   0   0   0   0
## ASV_3326   0   0   0   0   0   0   0   0
## ASV_1572   0   0   0   0   0   0   0   0
## ASV_1315   0   0   0   0   0   0   1   0
## ASV_3266   0   0   0   1   0   0   0   0
## ASV_727    2   0   1   1   1   1   0   0
## ASV_2479   0   0   0   0   0   0   0   0
## ASV_1570   0   0   0   0   0   0   0   0
## ASV_1257   0   0   0   0   0   0   0   0
## ASV_1826   0   0   0   0   0   0   0   0
## ASV_4222   0   0   0   0   0   0   0   0
## ASV_612    1   0   0   0   0   0   0   0
## ASV_2625   0   0   0   0   0   0   0   0
## ASV_3203   0   0   0   0   0   0   0   0
## ASV_2739   0   0   0   0   0   1   0   0
## ASV_3861   0   0   0   0   0   0   0   0
## ASV_3258   0   0   0   0   0   0   0   0
## ASV_2612   0   0   0   0   0   0   0   0
## ASV_1761   1   0   0   0   0   0   0   0
## ASV_2122   0   0   0   0   0   0   0   0
## ASV_1879   0   0   0   1   1   0   0   0
## ASV_2100   0   0   0   0   0   0   0   2
## ASV_409    0   0   0   0   0   0   0   1
## ASV_4093   0   0   0   0   0   0   0   0
## ASV_2353   0   0   0   0   0   0   0   0
## ASV_594    0   0   0   0   1   0   0   0
## ASV_2831   0   0   0   0   0   0   0   0
## ASV_743    0   0   0   0   0   0   0   0
## ASV_1877   0   1   0   0   0   0   0   0
## ASV_1428   0   0   0   0   0   0   0   0
## ASV_1620   0   0   0   0   0   0   0   0
## ASV_4680   0   0   0   0   0   0   0   0
## ASV_2984   0   0   0   0   0   0   0   0
## ASV_3303   0   0   0   0   0   0   0   0
## ASV_3402   0   0   0   0   0   0   0   0
## [1] 20

Flexilinea is the only Genus found in the phylum Chloroflexi in this data set. It also seems like there are a number of ASVs that don’t have an reads in fecal samples. Let’s look at the ASV level.

We will look into Euryarchaeota ASVs a bit more now.

## [1] 12
##                                                                                                               ASV_1308 
##                      "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter" 
##                                                                                                               ASV_3184 
##                          "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera" 
##                                                                                                                ASV_484 
##                      "Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter" 
##                                                                                                               ASV_3936 
## "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae_Candidatus_Methanomethylophilus" 
##                                                                                                                ASV_231 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_3478 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                                ASV_657 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_2010 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_2978 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_2521 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_3242 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae" 
##                                                                                                               ASV_3537 
##                                 "Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae"
## OTU Table:          [12 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_3936   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_231   13   3   1   5   7   3   8  15   7   3   4   5   0   0   0   0
## ASV_3478   1   1   0   0   0   1   0   0   0   1   1   0   0   0   0   0
## ASV_657    1   0   0   1   1   1   2   1   3   0   3   0   0   0   0   0
## ASV_2010   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1584   0   0   0   0   0   0   4   0   0   0   0   0   0   0   2   0
## ASV_2978   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1603   0   2   1   0   1   2   0   0   0   0   1   0   0   0   0   0
## ASV_2521   0   0   1   0   0   0   1   0   0   2   0   0   0   0   0   0
## ASV_3242   1   0   1   1   0   0   1   0   0   0   1   1   0   0   0   0
## ASV_3537   0   0   0   0   1   1   0   0   0   0   0   0   0   0   0   0
## ASV_3875   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
##          370 371 372 373 374 375 376 378
## ASV_3936   0   0   0   0   0   0   0   0
## ASV_231    0   0   0   0   0   0   0   0
## ASV_3478   0   0   0   0   0   0   0   0
## ASV_657    0   0   0   0   0   0   0   0
## ASV_2010   0   0   0   0   0   0   0   0
## ASV_1584   0   0   0   0   0   0   0   0
## ASV_2978   0   0   0   0   0   0   0   0
## ASV_1603   0   1   0   0   0   0   0   0
## ASV_2521   0   0   0   0   0   0   0   0
## ASV_3242   0   0   0   0   0   0   0   0
## ASV_3537   0   0   0   0   0   0   0   0
## ASV_3875   0   0   0   1   0   0   0   0
## OTU Table:          [2 taxa and 24 samples]
##                      taxa are rows
##          293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369
## ASV_1434   0   0   0   0   0   0   0   0   0   0   0   0   0   0   4  18
## ASV_4298   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
##          370 371 372 373 374 375 376 378
## ASV_1434   3   5   4   5   5   9   7  21
## ASV_4298   0   1   2   0   1   0   0   0

There are increased amounts of Methanocorpusculum in one ASV, but the other ASV has low amounts so it seems like not a strong enough association to bring this up.

Based on the DPCoA the phyla Spirochaetes and Actinobacteria also play and important role in distinguishing feces from grab samples.

# of Significant ASVs by Phyla
Var1 Freq
Firmicutes_Lachnospiraceae 32
Firmicutes_Ruminococcaceae 23
Bacteroidetes_Prevotellaceae 7
Firmicutes_Erysipelotrichaceae 7
Firmicutes_Family_XIII 4
Bacteroidetes_Rikenellaceae 3
Actinobacteria_Atopobiaceae 2
Actinobacteria_Eggerthellaceae 2
Euryarchaeota_Methanobacteriaceae 2
Firmicutes_Acidaminococcaceae 2
Firmicutes_Veillonellaceae 2
Planctomycetes_Pirellulaceae 2
Proteobacteria_Desulfovibrionaceae 2
Proteobacteria_Succinivibrionaceae 2
Actinobacteria_Coriobacteriales_Incertae_Sedis 1
Actinobacteria_Corynebacteriaceae 1
Bacteroidetes_Bacteroidaceae 1
Bacteroidetes_Tannerellaceae 1
Chloroflexi_Anaerolineaceae 1
Elusimicrobia_Elusimicrobiaceae 1
Elusimicrobia_Endomicrobiaceae 1
Epsilonbacteraeota_Campylobacteraceae 1
Euryarchaeota_Methanocorpusculaceae 1
Fibrobacteres_Fibrobacteraceae 1
Firmicutes_Christensenellaceae 1
Firmicutes_Clostridiaceae_1 1
Firmicutes_Defluviitaleaceae 1
Firmicutes_Eubacteriaceae 1
Firmicutes_Peptostreptococcaceae 1
Firmicutes_Streptococcaceae 1
Proteobacteria_Burkholderiaceae 1
Proteobacteria_Devosiaceae 1
Spirochaetes_Spirochaetaceae 1
Synergistetes_Synergistaceae 1
Tenericutes_Anaeroplasmataceae 1
Verrucomicrobia_Akkermansiaceae 1

From this we can see that Lachnospiraceae, Ruminococcaceae, Prevotellaceae and Erysipelotrichaceae were the most common families to be differentially abundant in feces compared to grab samples. We will take a closer look at all ASVs differentially abundant.

Differentially Abundant Taxa
p_value ASV Taxa
1 1.51e-03 ASV_1 Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group
2 1.51e-03 ASV_10 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans
3 1.51e-03 ASV_1006 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Candidatus_Soleaferrea
4 1.51e-03 ASV_1014 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax
5 1.51e-03 ASV_1016 Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis
6 1.51e-03 ASV_103 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1
7 1.51e-03 ASV_105 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group
8 1.51e-03 ASV_1098 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014
10 1.51e-03 ASV_1118 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_4
11 1.51e-03 ASV_1130 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018
12 1.51e-03 ASV_1132 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group
13 1.51e-03 ASV_1169 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Syntrophococcus
15 1.51e-03 ASV_1220 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_5
16 1.51e-03 ASV_1221 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium
17 1.51e-03 ASV_124 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group
18 1.51e-03 ASV_1256 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group
20 1.51e-03 ASV_13 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group
21 1.51e-03 ASV_1325 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009
23 1.51e-03 ASV_14 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium
25 1.51e-03 ASV_149 Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio
26 1.51e-03 ASV_1563 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium
28 1.51e-03 ASV_168 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Turicibacter
29 1.51e-03 ASV_1682 Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1
30 1.51e-03 ASV_1688 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_GCA-900066225
31 1.51e-03 ASV_172 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809
32 1.51e-03 ASV_184 Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera
33 1.51e-03 ASV_1882 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia
35 1.51e-03 ASV_199 Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella
36 1.51e-03 ASV_2 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group
37 1.51e-03 ASV_201 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group
38 1.51e-03 ASV_204 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Dorea
41 1.51e-03 ASV_210 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10
42 1.51e-03 ASV_2189 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001
43 1.51e-03 ASV_22 Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella
46 1.51e-03 ASV_227 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella
47 1.51e-03 ASV_23 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1
50 1.51e-03 ASV_235 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1
52 1.51e-03 ASV_246 Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma
53 1.51e-03 ASV_247 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-009
54 1.51e-03 ASV_25 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio
55 1.51e-03 ASV_254 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010
57 1.51e-03 ASV_26 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004
58 1.51e-03 ASV_267 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013
60 1.51e-03 ASV_3 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005
61 1.51e-03 ASV_3005 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Hydrogenoanaerobacterium
63 1.51e-03 ASV_311 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella
64 1.51e-03 ASV_320 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10
65 1.51e-03 ASV_330 Bacteria_Verrucomicrobia_Verrucomicrobiae_Verrucomicrobiales_Akkermansiaceae_Akkermansia
66 1.51e-03 ASV_335 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_dgA-11_gut_group
67 1.51e-03 ASV_344 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group
68 1.51e-03 ASV_348 Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011
69 1.51e-03 ASV_357 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002
70 1.51e-03 ASV_36 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Bacteroidaceae_Bacteroides
71 1.51e-03 ASV_37 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter
73 1.51e-03 ASV_376 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group
77 1.51e-03 ASV_409 Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea
78 1.51e-03 ASV_418 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium
79 1.51e-03 ASV_442 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Phascolarctobacterium
81 1.51e-03 ASV_457 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008
82 1.51e-03 ASV_471 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium
83 1.51e-03 ASV_48 Bacteria_Firmicutes_Clostridia_Clostridiales_Peptostreptococcaceae_Romboutsia
84 1.51e-03 ASV_510 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Alloprevotella
85 1.51e-03 ASV_52 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1
86 1.51e-03 ASV_524 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002
88 1.51e-03 ASV_560 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6
90 1.51e-03 ASV_57 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia
91 1.51e-03 ASV_60 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Alistipes
92 1.51e-03 ASV_601 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009
93 1.51e-03 ASV_622 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Oribacterium
94 1.51e-03 ASV_656 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter
96 1.51e-03 ASV_674 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera
97 1.51e-03 ASV_68 Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter
98 1.51e-03 ASV_7 Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanobrevibacter
99 1.51e-03 ASV_71 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2
100 1.51e-03 ASV_724 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Incertae_Sedis
102 1.51e-03 ASV_783 Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_p-1088-a5_gut_group
103 1.51e-03 ASV_795 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001
104 1.51e-03 ASV_8 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum
106 1.51e-03 ASV_815 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004
107 1.51e-03 ASV_819 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Flavonifractor
108 1.51e-03 ASV_837 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Agathobacter
109 1.51e-03 ASV_886 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group
111 1.51e-03 ASV_90 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella
112 1.51e-03 ASV_902 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002
113 1.51e-03 ASV_953 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group
114 1.51e-03 ASV_963 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Anaerosporobacter
9 2.77e-03 ASV_1100 Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium
14 2.77e-03 ASV_117 Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus
19 2.77e-03 ASV_1258 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-006
27 2.77e-03 ASV_1615 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006
80 2.77e-03 ASV_450 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter
87 2.77e-03 ASV_534 Bacteria_Proteobacteria_Alphaproteobacteria_Rhizobiales_Devosiaceae_Devosia
95 2.77e-03 ASV_66 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum
110 2.77e-03 ASV_893 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Oscillibacter
59 4.06e-03 ASV_29 Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_Treponema_2
101 4.06e-03 ASV_757 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_1
22 4.96e-03 ASV_1366 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio
24 4.96e-03 ASV_1434 Archaea_Euryarchaeota_Methanomicrobia_Methanomicrobiales_Methanocorpusculaceae_Methanocorpusculum
40 4.96e-03 ASV_2079 Bacteria_Epsilonbacteraeota_Campylobacteria_Campylobacterales_Campylobacteraceae_Campylobacter
44 4.96e-03 ASV_2217 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Tannerellaceae_Parabacteroides
49 4.96e-03 ASV_2319 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Fusicatenibacter
51 4.96e-03 ASV_2357 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Sporobacter
56 4.96e-03 ASV_2540 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_Denitrobacterium
74 4.96e-03 ASV_3830 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelatoclostridium
105 4.96e-03 ASV_80 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group
76 7.30e-03 ASV_3930 Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Fretibacterium
89 7.30e-03 ASV_563 Bacteria_Elusimicrobia_Endomicrobia_Endomicrobiales_Endomicrobiaceae_Candidatus_Endomicrobium
48 1.31e-02 ASV_2306 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-001
75 1.31e-02 ASV_3902 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_UBA1819
34 1.88e-02 ASV_1915 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_FD2005
45 1.88e-02 ASV_2220 Bacteria_Planctomycetes_Planctomycetacia_Pirellulales_Pirellulaceae_Pirellula
62 1.97e-02 ASV_303 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003
72 2.30e-02 ASV_3758 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Caproiciproducens
39 2.62e-02 ASV_2068 Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium_1

These are taxa that are differentailly abundant between grab samples and feces and their false discovery corrected p-value. ASVs are listed by significance.

## OTU Table:          [1 taxa and 24 samples]
##                      taxa are rows
##       293 294 295 296 297 298 299 300 301 302 303 304 366 367 368 369 370
## ASV_1 114 124 177 280 224 295 298 281 230 204 170 216   4   8   4   7   8
##       371 372 373 374 375 376 378
## ASV_1   8   6   5   9   4   0   1
## 
## Call:
## bbdml(formula = ASV_1 ~ Sample_Type + CowID + Day, phi.formula = ~1, 
##     data = ps_sub_gen)
## 
## 
## Coefficients associated with abundance:
##                  Estimate Std. Error t value         Pr(>|t|)    
## (Intercept)      -1.47780    0.07625 -19.380 0.00000000000155 ***
## Sample_TypeFeces -0.95570    0.06216 -15.375 0.00000000005273 ***
## CowIDCow_2477     0.18844    0.08258   2.282           0.0365 *  
## CowIDCow_2549    -0.05694    0.08660  -0.657           0.5202    
## CowIDCow_796      0.15162    0.08276   1.832           0.0856 .  
## DayDay_7         -0.07839    0.07259  -1.080           0.2962    
## DayDay_9          0.04504    0.07120   0.633           0.5359    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value        Pr(>|t|)    
## (Intercept)   -6.089      0.312  -19.52 0.0000000000014 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -143.94

This is the feature table for ASV_1, let’s graph out this most significantly differentially abundant ASV Christensenellaceae_R-7_group. There is significantly less of this taxa in feces compared to grab samples. The day did not effect this, but there was significant cow differences in abundance.

Here we see that Christensenellaceae_R-7_group is more abundant in feces vs grab samples. In fact if we look at the feature table above we see this taxa is almost not present in the rumen grab samples.

Grab Samples vs other rumen samples

We will remove other a few sample types to compress the data down and look just at the grab sample and stomach tube.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 4690 taxa and 56 samples ]
## sample_data() Sample Data:       [ 56 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 4690 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 4690 tips and 4688 internal nodes ]

After subsetting the data we have 4,690 ASVs in 56 samples.

Metrics after filtering

## [1] 4690
## [1] 20
## [1] 74
## [1] 110
## [1] 279

Previously, there are 5485 ASVs in the dataset. This was composed of 21 phyla, 78 Orders, 116 Families and 293 Genera. In the new subset we have 4690 ASVs in the dataset. This is composed of 20 phyla, 74 Orders, 110 Families and 279 Genera.

Exploratory Analysis

Again we will transformed the data for some exploratory analysis.

## Scale for 'colour' is already present. Adding another scale for
## 'colour', which will replace the existing scale.

Here we begin to see that Stomach Tube samples are more variable than the grab sample. Liquid strained samples seem to be the most variable (maybe comprable to stomach tube samples). Additionally, there seems to be two clusters for stomach tube samples (it’s probably not significant though). Potentially due to the presence of fiber in the sample or not?

From the eigenvalues we can see that 2 axis is appropriate for graphing, together explaining almost 90% of the variance between the samples.

Now that we take into account phylogenetic information in the distance metric there is a lot more variation explained. The first Axsis contains more variation that the second and mostly separates liquid (strained and unstrained) and some stomach tube samples from solid and grab samples.

Let’s make a figure with Weighted unifrac with and without the fecal samples

The eigenvalues here show the variation is spread across many axis, thus a 3D graph is best. You can find it hosted online here.

## No trace type specified:
##   Based on info supplied, a 'scatter3d' trace seems appropriate.
##   Read more about this trace type -> https://plot.ly/r/reference/#scatter3d
## No scatter3d mode specifed:
##   Setting the mode to markers
##   Read more about this attribute -> https://plot.ly/r/reference/#scatter-mode

As before less of the variation is explained in each axis with the unweighted versus the weighted unifrac. Thus it seems that the difference between sample types is due to abundance differences and less about differences in species. We also, see the two clusters of stomach tube samples appearing again. This strengthens the hypothesis that stomach tube samples are more variable than grab samples and that there a minor taxa that explain differences between stomach tube samples. Addtionally, it looks like the two clusters of stomach tube samples might be forming due to individual cow differences (not a breed difference). Liquid sample remain different from grab and stomach tube samples.

The eigenvalues here show 2 axis are sufficient to capture most of the total variation.

We see again that the 1st axis corresponds is separtating liquid strained and unstrained samples from other rumen samples. This plot suggest there are more Bacteroidetes and Kiritimatiellaeota in the liquid samples, while rumen samples have more Firmicutes. This can also be seen in the first DPCoA we made where we said that Liquid samples have more Bacteroidetes and less Firmicutes than other rumen sample types. Thus, we will probably only need to have one DPCoA graph in the paper.

We should see what taxa are differentially more or less abundant in grab sample vs other rumen sample types.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 278 taxa and 56 samples ]
## sample_data() Sample Data:       [ 56 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 278 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 278 tips and 277 internal nodes ]

There are 278 genera in the rumen sample types.

99 taxa could not be fit with the model, but 179 were fit to the model and 108 were significantly differentially abundant genera p<0.05. 87 were significantly differentially abundant genera p<0.01. Lastly, 87 were significantly differentially abundant taxa p<0.05.

First, we will check if into the genera could not be fit to the model and see if we can determine why.

## OTU Table:          [99 taxa and 56 samples]
##                      taxa are rows
##          282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_5569   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_204    0   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_4099   1   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_878    4   9   0   0   2   0   0   0   1   2   1   6   5   4   0   0
## ASV_5218   0   1   0   1   0   0   0   0   0   0   0   0   0   0   2   0
## ASV_724    0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_5230   0   0   0   2   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5009   0   1   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_2417   2   1   2   2   1   0   0   0   0   0   1   0   0   1   0   0
## ASV_2322   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_113    0   0   2   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_147    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5397   0   0   0   0   0   0   0   3   2   0   2   0   0   0   0   0
## ASV_4951   0   1   1   1   0   0   2   4   0   0   0   0   0   0   0   0
## ASV_5246   0   0   0   0   0   0   0   0   2   0   0   0   0   0   0   0
## ASV_4383   0   0   1   0   2   0   1   1   2   2   0   0   0   0   1   2
## ASV_5288   0   2   0   0   1   0   0   0   0   0   1   0   0   0   1   2
## ASV_5123   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1258   1   4   1   0   3   3   1   0  11   1   1   1   1   1   2   2
## ASV_5496   2   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_4673   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3469   1   0   0   0   0   1   1   1   0   0   0   0   0   1   0   0
## ASV_4670   0   2   1   0   2   0   0   0   0   0   0   0   0   0   0   0
## ASV_5204   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4857   0   1   5   0   0   1   2   0   2   0   0   0   0   0   0   0
## ASV_5547   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4998   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4508   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_2399   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5206   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1728   0   0   3   0   0   1   0   0   0   0   0   0   0   1   0   0
## ASV_1078   0   5   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_4258   1   1   8   2   2   1   0   0   1   0   1   0   0   0   0   0
## ASV_2658   0   0   0   0   0   0   1   0   0   0   0   0   0   1   0   0
## ASV_2389   2   1   0   1   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_1853   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4912   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5382   0   0   0   3   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2915   0   0  16   4   5   3   1   1   0   0   0   0   0   0   1   0
## ASV_4015   1   0   0   1   5   1   1   1   2   2   0   1   0   1   0   0
## ASV_4126   0   0   3   3   0   0   0   0   0   0   0   0   0   0   0   2
## ASV_4688   0   0   1   0   1   3   2   1   0   0   0   0   0   0   0   0
## ASV_4324   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4605   0   0   0   0   0   2   0   1   0   0  12   0   0   0   0   0
## ASV_5222   0   0   2   1   2   0   0   1   1   0   0   0   0   0   0   1
## ASV_5594   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3987   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5262   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_2401   0   0   1   4   0   0   0   0   0   0   0   0   1   0   0   1
## ASV_4992   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_1856   0   0   1   0   2   0   0   0   0   0   2   0   0   0   0   0
## ASV_3262   0   0   1   0   1   1   0   0   0   0   0   0   0   1   0   0
## ASV_5025   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4151   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4913   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3684   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4353   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4378   0   1   0   0   1   0   0   0   1   0   0   0   0   0   0   0
## ASV_1247   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3201   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_2076   0   0   0   0   3   1   0   0   0   0   0   0   0   0   0   0
## ASV_3120   0   0   1   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_2445   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1307   0   2   0   0   0   1   0   0   1   0   0   0   0   0   0   0
## ASV_5210   1   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2550   2   0   0   0   0   2   1   0   0   0   0   0   0   0   0   0
## ASV_4422   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3119   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5444   0   2   0   0   0   0   0   1   0   0   0   0   1   0   0   1
## ASV_2687   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4612   0   0   0   0   0   0   0   0   1   0   0   0   0   0   1   0
## ASV_5614   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1213   0   0   0   0   0   0   0   0   0   0   0   1   1   0   0   0
## ASV_5192   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5595   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4629   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5584   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5568   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3905   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5108   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5036   1   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_5532   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5269   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4849   1   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_3829   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1688   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_1756   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4267   0   3   1   1   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_4142   0   0   0   0   0   1   0   0   1   0   0   0   0   0   0   0
## ASV_4771   1   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_5492   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3902   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_4822   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_893    0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_1679   1   2   0   0   2   0   0   0   0   0   0   0   0   0   0   0
## ASV_4340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##          298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_5569   0   0   0   0   0   0   3   0   0   0   0   0   0   0   0   0
## ASV_204    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4099   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_878    3   0   0   0   4   6   2   4   2   2   2   0   3   0   2   4
## ASV_5218   0   0   0   1   0   0   0   0   0   0   0   0   0   0   2   0
## ASV_724    0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5230   0   0   0   0   0   0   0   0   0   0   0   3   0   0   0   0
## ASV_5009   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2417   0   0   0   0   1   0   1   2   2   3   2   2   2   0   1   1
## ASV_2322   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_113    0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_147    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5397   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4951   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_5246   0   0   0   0   0   0   0   0   0   0   0   0   1   0   1   0
## ASV_4383   1   0   0   0   0   1   0   0   0   0   1   1   1   0   0   0
## ASV_5288   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_5123   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_1258   4   2   0   1   2   1   5   0   1   2   2   0   0   0   2   4
## ASV_5496   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4673   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3469   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_4670   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5204   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4857   0   0   0   0   0   0   0   0   0   0   2   0   0   0   0   0
## ASV_5547   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4998   0   0   0   0   0   0   0   0   0   0   0   0   3   0   0   0
## ASV_4508   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2399   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_5206   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1728   0   0   0   0   0   0   0   0   2   0   1   0   0   1   0   2
## ASV_1078   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_4258   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_2658   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   1
## ASV_2389   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_1853   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_4912   0   0   0   0   0   0   0   0   0   0   1   1   0   0   0   0
## ASV_5382   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2915   0   0   0   0   0   0   0   1   0   0   0   1   1   0   1   0
## ASV_4015   0   0   0   0   0   0   0   0   0   0   0   0   1   0   1   1
## ASV_4126   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_4688   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_4324   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0
## ASV_4605   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5222   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_5594   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_3987   1   0   0   0   0   0   0   0   0   0   0   1   6   0   0   0
## ASV_5262   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_2401   0   0   0   0   0   0   0   0   0   0   0   5   0   2   0   0
## ASV_4992   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1856   1   0   0   1   0   0   0   2   0   0   0   0   0   0   0   0
## ASV_3262   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   1
## ASV_5025   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4151   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_4913   0   0   0   0   0   0   0   0   0   0   0   0   0   0   2   0
## ASV_3684   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4353   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4378   0   0   0   0   0   0   0   0   0   1   0   1   0   0   0   0
## ASV_1247   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3201   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2076   0   0   0   0   0   0   0   3   0   0   0   0   0   0   0   1
## ASV_3120   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2445   0   0   0   0   0   0   0   0   0   1   0   0   1   0   0   0
## ASV_1307   0   0   0   0   1   0   0   1   0   0   0   1   1   0   0   0
## ASV_5210   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2550   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4422   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_3119   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0
## ASV_5444   0   1   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_2687   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_4612   1   0   0   0   0   0   0   0   0   1   1   0   0   0   0   0
## ASV_5614   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1213   0   0   0   0   0   1   0   0   0   0   2   0   1   0   0   3
## ASV_5192   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5595   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_4629   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5584   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5568   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3905   0   0   1   0   0   1   0   0   0   0   0   0   0   1   0   0
## ASV_5108   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5036   0   1   0   0   2   0   0   0   0   1   0   0   0   0   0   0
## ASV_5532   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5269   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4849   0   0   0   0   0   0   1   1   0   0   0   0   0   0   0   0
## ASV_3829   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1688   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1756   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4267   0   0   1   0   1   0   0   0   0   0   0   0   0   0   1   0
## ASV_4142   0   0   0   0   0   0   0   0   1   0   0   1   1   0   0   0
## ASV_4771   0   1   0   0   0   0   1   0   0   0   0   0   0   0   0   0
## ASV_5492   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3902   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4822   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_893    0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_1679   0   0   0   0   0   0   0  11   5   9   3   3   9   0   0   3
## ASV_4340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
##          360 361 362 363 365 379 380 381 382 383 384 385 386 387 388 389
## ASV_5569   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_204    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4099   0   0   0   1   0   0   0   0   0   0   0   0   1   0   0   3
## ASV_878    1   4   0   0   0   6  10   2   0   2   5   0   0   0   2   8
## ASV_5218   1   1   0   0   0   0   0   0   0   0   0   0   0   1   0   2
## ASV_724    0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_5230   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5009   0   0   1   0   0   0   0   0   0   0   3   0   0   0   0   0
## ASV_2417   1   0   0   0   2   0   0   0   1   0   0   0   0   0   0   0
## ASV_2322   1   0   1   0   0   0   0   0   0   0   1   1   0   0   0   0
## ASV_113    0   1   0   0   0   1   0   0   0   0   1   0   0   0   1   0
## ASV_147    0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5397   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4951   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5246   0   1   0   0   0   0   0   0   2   1   0   0   0   0   0   0
## ASV_4383   1   1   0   0   0   0   0   0   2   0   1   1   0   0   0   1
## ASV_5288   1   0   0   0   0   0   0   0   1   0   1   0   0   0   0   0
## ASV_5123   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_5340   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_1258   1   4   4   2   1   1   2   7   6   1   2   3   2   1   5   1
## ASV_5496   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   1
## ASV_4673   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3469   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_4670   0   0   0   0   0   0   0   1   1   0   0   0   0   0   0   0
## ASV_5204   0   0   0   0   0   0   0   2   0   0   0   1   0   0   0   0
## ASV_4857   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5547   0   3   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_4998   0   2   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4508   1   0   1   0   0   0   0   0   0   0   4   0   0   0   1   1
## ASV_2399   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5206   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1728   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1078   0   4   0   0   0   0   1   0   0   0   0   0   1   0   0   0
## ASV_4258   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2658   0   1   0   0   0   0   0   1   0   1   0   0   0   0   0   1
## ASV_2389   2   0   0   1   0   0   1   0   1   0   0   1   0   0   0   0
## ASV_1853   0   1   0   0   0   0   0   0   0   1   0   0   0   0   0   1
## ASV_4912   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5382   2   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2915   1   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_4015   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4126   4   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0
## ASV_4688   0   0   2   0   0   0   0   0   0   0   0   0   1   2   0   0
## ASV_4324   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_4605   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5222   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5594   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_3987   0   6   0   0   0   0   0   0   0   0  11   0   0   0   0   0
## ASV_5262   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2401   7   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4992   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_1856   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0
## ASV_3262   0   0   0   0   0   1   0   0   3   1   1   0   0   0   0   0
## ASV_5025   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0   0
## ASV_4151   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1
## ASV_4913   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_3684   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4353   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4378   1   0   0   0   1   0   0   0   2   0   0   0   3   0   0   1
## ASV_1247   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3201   0   0   0   0   0   0   0   0   1   0   2   0   0   0   0   0
## ASV_2076   0   0   1   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_3120   0   0   0   0   0   1   0   0   0   0   0   0   0   0   0   0
## ASV_2445   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_1307   0   0   0   0   0   2   0   0   0   0   0   0   0   0   0   0
## ASV_5210   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2550   1   0   0   0   0   0   0   0   0   0   0   0   1   0   1   0
## ASV_4422   0   0   0   1   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3119   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5444   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_2687   0   0   0   0   0   0   0   1   0   0   0   0   1   0   0   0
## ASV_4612   0   0   0   0   0   1   0   1   2   2   0   1   2   0   1   0
## ASV_5614   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1213   1   0   1   0   0   0   0   0   1   0   0   0   1   0   0   0
## ASV_5192   0   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0
## ASV_5595   0   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4629   1   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5584   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_5568   0   0   0   0   0   0   0   0   0   0   0   0   0   1   0   0
## ASV_3905   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_5108   1   0   0   0   0   0   1   0   0   0   0   0   0   0   1   0
## ASV_5036   0   0   0   0   0   2   0   0   0   0   1   1   1   0   0   0
## ASV_5532   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_5269   0   3   0   0   0   0   0   0   1   0   4   0   0   0   0   0
## ASV_4849   0   0   1   0   1   0   0   0   0   0   0   0   0   0   0   0
## ASV_3829   0   0   0   0   0   0   0   0   0   0   1   0   0   0   0   0
## ASV_1688   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_1756   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_4267   0   1   0   0   1   3   1   0   1   0   0   0   3   1   1   0
## ASV_4142   0   0   0   0   0   0   1   0   2   0   0   0   1   0   0   1
## ASV_4771   0   0   1   0   0   0   0   0   0   0   0   0   3   0   1   0
## ASV_5492   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_3902   0   0   0   0   0   0   0   0   1   0   0   0   0   0   0   0
## ASV_4822   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
## ASV_893    0   0   0   0   0   0   0   0   0   0   0   0   1   0   0   0
## ASV_1679   8   2   2   2   4   0   0   0   0   0   0   0   0   0   0   0
## ASV_4340   0   0   0   0   0   0   0   0   0   0   2   0   0   0   1   0
##          390 505 506 507 508 509 510 511
## ASV_5569   0   0   0   0   0   0   0   0
## ASV_204    0   0   0   0   0   1   0   0
## ASV_4099   0   0   0   1   0   0   0   0
## ASV_878    0   0   0   3   0   6   6   7
## ASV_5218   0   0   0   0   0   0   1   0
## ASV_724    0   0   0   0   0   1   1   0
## ASV_5230   0   0   1   0   0   1   0   0
## ASV_5009   0   0   0   0   0   0   0   0
## ASV_2417   0   0   0   2   0   8   1   3
## ASV_2322   0   0   0   0   0   2   0   0
## ASV_113    0   0   1   0   0   0   0   0
## ASV_147    0   0   0   0   0   0   1   0
## ASV_5397   0   0   0   0   0   0   0   0
## ASV_4951   0   0   0   0   0   0   0   0
## ASV_5246   0   0   0   0   1   0   0   0
## ASV_4383   0   0   0   0   0   2   0   1
## ASV_5288   0   0   0   0   0   0   0   0
## ASV_5123   0   0   0   0   0   1   0   0
## ASV_5340   0   0   0   0   0   3   1   0
## ASV_1258   2   0   2   0   0   4   0   1
## ASV_5496   0   0   0   0   0   0   0   0
## ASV_4673   0   0   0   0   0   0   0   0
## ASV_3469   0   0   0   0   0   2   1   0
## ASV_4670   0   0   0   0   1   0   0   0
## ASV_5204   0   0   0   0   0   1   1   0
## ASV_4857   0   0   0   0   0   0   0   0
## ASV_5547   0   0   0   0   0   0   0   0
## ASV_4998   0   0   0   0   0   1   0   0
## ASV_4508   0   0   0   0   1   2   0   0
## ASV_2399   0   0   0   0   0   0   1   0
## ASV_5206   0   0   0   0   0   1   0   0
## ASV_1728   0   0   0   0   0   1   0   0
## ASV_1078   0   0   0   0   0   0   0   0
## ASV_4258   0   0   0   0   0   0   0   0
## ASV_2658   0   0   0   0   0   0   1   0
## ASV_2389   0   0   0   0   0   1   0   0
## ASV_1853   0   1   0   0   0   0   1   0
## ASV_4912   0   0   0   0   0   0   0   0
## ASV_5382   0   0   0   0   0   2   0   0
## ASV_2915   0   0   0   0   0   0   0   0
## ASV_4015   0   0   1   0   0   0   0   0
## ASV_4126   0   0   0   0   1   0   0   1
## ASV_4688   0   0   1   0   0   0   0   0
## ASV_4324   0   0   0   0   0   1   0   0
## ASV_4605   0   0   0   0   1   0   0   0
## ASV_5222   0   0   0   0   0   0   0   0
## ASV_5594   0   0   0   0   0   0   0   0
## ASV_3987   0   0   0   0   0   0   0   0
## ASV_5262   0   0   0   0   0   0   0   0
## ASV_2401   0   1   0   0   0   1   0   0
## ASV_4992   0   0   1   0   0   0   0   0
## ASV_1856   2   0   0   0   1   1   0   0
## ASV_3262   0   0   1   0   0   0   0   0
## ASV_5025   0   0   0   0   0   0   0   0
## ASV_4151   0   0   0   0   0   0   0   0
## ASV_5107   0   0   0   0   1   0   0   1
## ASV_4913   0   0   0   0   0   1   0   2
## ASV_3684   0   0   0   0   0   0   1   0
## ASV_4353   0   0   0   0   0   0   0   1
## ASV_4378   0   0   0   0   0   2   0   1
## ASV_1247   0   0   0   0   0   0   2   0
## ASV_3201   0   0   0   0   0   0   0   0
## ASV_2076   0   0   0   0   0   0   0   0
## ASV_3120   0   0   0   0   0   0   0   2
## ASV_2445   0   0   0   0   0   0   0   0
## ASV_1307   0   0   0   0   0   0   0   0
## ASV_5210   0   0   0   0   0   0   0   0
## ASV_2550   0   0   2   0   0   1   1   0
## ASV_4422   0   0   0   0   0   1   0   2
## ASV_3119   0   0   1   0   0   1   0   0
## ASV_5444   0   0   0   1   0   0   0   0
## ASV_2687   0   0   0   0   0   0   2   2
## ASV_4612   0   1   0   0   0   0   0   0
## ASV_5614   0   0   0   0   0   2   0   0
## ASV_1213   0   0   1   0   0   1   0   0
## ASV_5192   0   0   0   0   0   0   0   0
## ASV_5595   0   0   0   0   0   0   0   0
## ASV_4629   0   0   0   0   0   0   0   0
## ASV_5584   0   0   0   0   0   0   0   1
## ASV_5568   0   0   0   0   0   0   1   0
## ASV_3905   0   0   0   0   0   0   2   0
## ASV_5108   0   0   0   0   0   0   0   0
## ASV_5036   0   0   0   0   0   0   0   0
## ASV_5532   0   0   0   0   0   0   0   0
## ASV_5269   0   0   0   0   0   0   0   0
## ASV_4849   0   0   0   0   0   1   0   0
## ASV_3829   0   0   0   0   0   0   0   0
## ASV_1688   0   0   0   0   0   0   0   0
## ASV_1448   0   0   0   0   0   0   0   0
## ASV_1756   0   0   0   0   0   0   1   0
## ASV_4267   0   0   0   0   0   0   0   0
## ASV_4142   1   0   0   1   1   1   1   2
## ASV_4771   0   0   0   0   0   3   1   0
## ASV_5492   0   0   1   0   0   0   0   0
## ASV_3902   0   0   0   0   0   1   0   0
## ASV_4822   0   1   0   0   0   0   0   0
## ASV_893    0   0   0   1   0   3   1   0
## ASV_1679   0   1   4   2   1  11   4  17
## ASV_4340   0   0   0   0   0   0   0   0

Yikes, 99 taxa could not be fit with the model, but this looks to be due to circumstances where there is very few reads for a particular ASV (thus, a model can’t be fit) or instances where there is only reads in one sample type.

Now, we will return to the corncob output. We can see a list of differentially-abundant taxa using:

##   [1] "Firmicutes_Lachnospiraceae_Lachnospiraceae_FE2018_group"              
##   [2] "Firmicutes_Lachnospiraceae_Lachnospiraceae_ND3007_group"              
##   [3] "Firmicutes_Lachnospiraceae_Lachnospiraceae_NK4A136_group"             
##   [4] "Firmicutes_Lachnospiraceae_Acetatifactor"                             
##   [5] "Firmicutes_Lachnospiraceae_Howardella"                                
##   [6] "Firmicutes_Lachnospiraceae_Marvinbryantia"                            
##   [7] "Firmicutes_Lachnospiraceae_Blautia"                                   
##   [8] "Firmicutes_Lachnospiraceae_Lachnospiraceae_NK3A20_group"              
##   [9] "Firmicutes_Lachnospiraceae_XBB1006"                                   
##  [10] "Firmicutes_Lachnospiraceae_Roseburia"                                 
##  [11] "Firmicutes_Lachnospiraceae_Shuttleworthia"                            
##  [12] "Firmicutes_Lachnospiraceae_Pseudobutyrivibrio"                        
##  [13] "Firmicutes_Lachnospiraceae_Lachnospiraceae_AC2044_group"              
##  [14] "Firmicutes_Lachnospiraceae_Moryella"                                  
##  [15] "Firmicutes_Lachnospiraceae_Butyrivibrio_2"                            
##  [16] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-002"                   
##  [17] "Firmicutes_Lachnospiraceae_Acetitomaculum"                            
##  [18] "Firmicutes_Lachnospiraceae_Lachnoclostridium_10"                      
##  [19] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-006"                   
##  [20] "Firmicutes_Lachnospiraceae_Coprococcus_2"                             
##  [21] "Firmicutes_Defluviitaleaceae_Defluviitaleaceae_UCG-011"               
##  [22] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-010"                   
##  [23] "Firmicutes_Lachnospiraceae_Coprococcus_1"                             
##  [24] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-008"                   
##  [25] "Firmicutes_Lachnospiraceae_Lachnospiraceae_FCS020_group"              
##  [26] "Firmicutes_Lachnospiraceae_Lachnospiraceae_UCG-009"                   
##  [27] "Firmicutes_Lachnospiraceae_Tyzzerella_3"                              
##  [28] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-014"                   
##  [29] "Firmicutes_Veillonellaceae_Veillonellaceae_UCG-001"                   
##  [30] "Firmicutes_Veillonellaceae_Quinella"                                  
##  [31] "Firmicutes_Veillonellaceae_Selenomonas_1"                             
##  [32] "Firmicutes_Veillonellaceae_Schwartzia"                                
##  [33] "Firmicutes_Veillonellaceae_Selenomonas_4"                             
##  [34] "Firmicutes_Veillonellaceae_Anaerovibrio"                              
##  [35] "Firmicutes_Family_XIII_Mogibacterium"                                 
##  [36] "Firmicutes_Family_XIII_Family_XIII_AD3011_group"                      
##  [37] "Firmicutes_Family_XIII_Family_XIII_UCG-001"                           
##  [38] "Firmicutes_Family_XIII_Anaerovorax"                                   
##  [39] "Tenericutes_Anaeroplasmataceae_Anaeroplasma"                          
##  [40] "Firmicutes_Erysipelotrichaceae_Catenisphaera"                         
##  [41] "Firmicutes_Erysipelotrichaceae_Solobacterium"                         
##  [42] "Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009"           
##  [43] "Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004"           
##  [44] "Firmicutes_Streptococcaceae_Streptococcus"                            
##  [45] "Firmicutes_Lactobacillaceae_Lactobacillus"                            
##  [46] "Firmicutes_Staphylococcaceae_Staphylococcus"                          
##  [47] "Firmicutes_Planococcaceae_Planococcus"                                
##  [48] "Firmicutes_Clostridiaceae_1_Clostridium_sensu_stricto_1"              
##  [49] "Firmicutes_Acidaminococcaceae_Succiniclasticum"                       
##  [50] "Firmicutes_Syntrophomonadaceae_Pelospora"                             
##  [51] "Firmicutes_Eubacteriaceae_Anaerofustis"                               
##  [52] "Elusimicrobia_Elusimicrobiaceae_Elusimicrobium"                       
##  [53] "Proteobacteria_Pseudomonadaceae_Pseudomonas"                          
##  [54] "Proteobacteria_Succinivibrionaceae_Succinimonas"                      
##  [55] "Proteobacteria_Succinivibrionaceae_Anaerobiospirillum"                
##  [56] "Proteobacteria_Succinivibrionaceae_Succinivibrio"                     
##  [57] "Proteobacteria_Burkholderiaceae_Sutterella"                           
##  [58] "Proteobacteria_Burkholderiaceae_Variovorax"                           
##  [59] "Proteobacteria_Burkholderiaceae_Massilia"                             
##  [60] "Proteobacteria_Cardiobacteriaceae_Suttonella"                         
##  [61] "Proteobacteria_Succinivibrionaceae_Ruminobacter"                      
##  [62] "Proteobacteria_Succinivibrionaceae_Succinivibrionaceae_UCG-002"       
##  [63] "Proteobacteria_Desulfobulbaceae_Desulfobulbus"                        
##  [64] "Fusobacteria_Fusobacteriaceae_Fusobacterium"                          
##  [65] "Euryarchaeota_Methanobacteriaceae_Methanosphaera"                     
##  [66] "Euryarchaeota_Methanomethylophilaceae_Candidatus_Methanomethylophilus"
##  [67] "Proteobacteria_Desulfovibrionaceae_Desulfovibrio"                     
##  [68] "Proteobacteria_Desulfovibrionaceae_Mailhella"                         
##  [69] "Proteobacteria_Desulfuromonadaceae_Desulfuromonas"                    
##  [70] "Spirochaetes_Spirochaetaceae_M2PT2-76_termite_group"                  
##  [71] "Actinobacteria_Corynebacteriaceae_Corynebacterium"                    
##  [72] "Actinobacteria_Nocardiaceae_Rhodococcus"                              
##  [73] "Actinobacteria_Coriobacteriales_Incertae_Sedis_Raoultibacter"         
##  [74] "Actinobacteria_Eggerthellaceae_DNF00809"                              
##  [75] "Actinobacteria_Atopobiaceae_Olsenella"                                
##  [76] "Actinobacteria_Atopobiaceae_Atopobium"                                
##  [77] "Fibrobacteres_Fibrobacteraceae_Fibrobacter"                           
##  [78] "Chloroflexi_Anaerolineaceae_Flexilinea"                               
##  [79] "Synergistetes_Synergistaceae_Pyramidobacter"                          
##  [80] "Firmicutes_Christensenellaceae_Christensenellaceae_R-7_group"         
##  [81] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-010"                   
##  [82] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-003"                  
##  [83] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-004"                  
##  [84] "Bacteroidetes_Prevotellaceae_Prevotellaceae_Ga6A1_group"              
##  [85] "Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-001"                  
##  [86] "Bacteroidetes_Prevotellaceae_Prevotella_1"                            
##  [87] "Bacteroidetes_Prevotellaceae_Prevotellaceae_NK3B31_group"             
##  [88] "Bacteroidetes_Prevotellaceae_Prevotellaceae_YAB2003_group"            
##  [89] "Bacteroidetes_Rikenellaceae_Rikenellaceae_RC9_gut_group"              
##  [90] "Bacteroidetes_Rikenellaceae_U29-B03"                                  
##  [91] "Bacteroidetes_Porphyromonadaceae_Porphyromonas"                       
##  [92] "Firmicutes_Ruminococcaceae_Ruminiclostridium_6"                       
##  [93] "Firmicutes_Ruminococcaceae_Ruminococcus_1"                            
##  [94] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-001"                   
##  [95] "Firmicutes_Ruminococcaceae_Ruminococcus_2"                            
##  [96] "Firmicutes_Ruminococcaceae_CAG-352"                                   
##  [97] "Firmicutes_Ruminococcaceae_Saccharofermentans"                        
##  [98] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-013"                   
##  [99] "Firmicutes_Ruminococcaceae_Ruminococcaceae_NK4A214_group"             
## [100] "Firmicutes_Ruminococcaceae_Papillibacter"                             
## [101] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-005"                   
## [102] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-002"                   
## [103] "Firmicutes_Ruminococcaceae_Ruminiclostridium_9"                       
## [104] "Firmicutes_Ruminococcaceae_Ruminococcaceae_V9D2013_group"             
## [105] "Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-004"                   
## [106] "Firmicutes_Lachnospiraceae_Lachnospiraceae_XPB1014_group"             
## [107] "Firmicutes_Lachnospiraceae_possible_genus_Sk018"                      
## [108] "Firmicutes_Lachnospiraceae_probable_genus_10"

There are 108 genera differentially abundant. We will look at the unique families they represent.

# of significant genera in each family
Var1 Freq
Firmicutes_Lachnospiraceae 29
Firmicutes_Ruminococcaceae 16
Bacteroidetes_Prevotellaceae 7
Firmicutes_Veillonellaceae 6
Proteobacteria_Succinivibrionaceae 5
Firmicutes_Erysipelotrichaceae 4
Firmicutes_Family_XIII 4
Proteobacteria_Burkholderiaceae 3
Actinobacteria_Atopobiaceae 2
Bacteroidetes_Rikenellaceae 2
Proteobacteria_Desulfovibrionaceae 2
Actinobacteria_Coriobacteriales_Incertae_Sedis 1
Actinobacteria_Corynebacteriaceae 1
Actinobacteria_Eggerthellaceae 1
Actinobacteria_Nocardiaceae 1
Bacteroidetes_Porphyromonadaceae 1
Chloroflexi_Anaerolineaceae 1
Elusimicrobia_Elusimicrobiaceae 1
Euryarchaeota_Methanobacteriaceae 1
Euryarchaeota_Methanomethylophilaceae 1
Fibrobacteres_Fibrobacteraceae 1
Firmicutes_Acidaminococcaceae 1
Firmicutes_Christensenellaceae 1
Firmicutes_Clostridiaceae_1 1
Firmicutes_Defluviitaleaceae 1
Firmicutes_Eubacteriaceae 1
Firmicutes_Lactobacillaceae 1
Firmicutes_Planococcaceae 1
Firmicutes_Staphylococcaceae 1
Firmicutes_Streptococcaceae 1
Firmicutes_Syntrophomonadaceae 1
Fusobacteria_Fusobacteriaceae 1
Proteobacteria_Cardiobacteriaceae 1
Proteobacteria_Desulfobulbaceae 1
Proteobacteria_Desulfuromonadaceae 1
Proteobacteria_Pseudomonadaceae 1
Spirochaetes_Spirochaetaceae 1
Synergistetes_Synergistaceae 1
Tenericutes_Anaeroplasmataceae 1

From this we can see that Lachnospiraceae, Ruminococcaceae, and Prevotellaceae were the most common families to be differentially abundant in grab samples vs other rumen sample types. We will take a closer look at all ASVs differentially abundant.

Differentially Abundant Taxa
p_value ASV Taxa
1 2.43e-03 ASV_1 Bacteria_Firmicutes_Clostridia_Clostridiales_Christensenellaceae_Christensenellaceae_R-7_group
2 2.43e-03 ASV_10 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Saccharofermentans
3 2.43e-03 ASV_1016 Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Anaerofustis
4 2.43e-03 ASV_103 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_1
5 2.43e-03 ASV_105 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_XPB1014_group
6 2.43e-03 ASV_1130 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_possible_genus_Sk018
7 2.43e-03 ASV_1132 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_NK3B31_group
8 2.43e-03 ASV_1161 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_XBB1006
9 2.43e-03 ASV_117 Bacteria_Firmicutes_Bacilli_Lactobacillales_Streptococcaceae_Streptococcus
10 2.43e-03 ASV_120 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-002
11 2.43e-03 ASV_124 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_AC2044_group
12 2.43e-03 ASV_1366 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Anaerovibrio
13 2.43e-03 ASV_1372 Bacteria_Fusobacteria_Fusobacteriia_Fusobacteriales_Fusobacteriaceae_Fusobacterium
15 2.43e-03 ASV_14 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Mogibacterium
16 2.43e-03 ASV_1403 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Howardella
17 2.43e-03 ASV_141 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrio
18 2.43e-03 ASV_145 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_AD3011_group
21 2.43e-03 ASV_154 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-004
25 2.43e-03 ASV_172 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Eggerthellaceae_DNF00809
26 2.43e-03 ASV_176 Bacteria_Proteobacteria_Gammaproteobacteria_Pseudomonadales_Pseudomonadaceae_Pseudomonas
27 2.43e-03 ASV_183 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-014
29 2.43e-03 ASV_192 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_V9D2013_group
30 2.43e-03 ASV_2 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK3A20_group
31 2.43e-03 ASV_20 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotella_1
32 2.43e-03 ASV_201 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_Ga6A1_group
33 2.43e-03 ASV_210 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_probable_genus_10
39 2.43e-03 ASV_2183 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Tyzzerella_3
40 2.43e-03 ASV_22 Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Sutterella
41 2.43e-03 ASV_2244 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Schwartzia
42 2.43e-03 ASV_23 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_1
44 2.43e-03 ASV_235 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_1
45 2.43e-03 ASV_2419 Bacteria_Proteobacteria_Gammaproteobacteria_Cardiobacteriales_Cardiobacteriaceae_Suttonella
46 2.43e-03 ASV_246 Bacteria_Tenericutes_Mollicutes_Anaeroplasmatales_Anaeroplasmataceae_Anaeroplasma
47 2.43e-03 ASV_248 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FCS020_group
48 2.43e-03 ASV_25 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Pseudobutyrivibrio
49 2.43e-03 ASV_2517 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Quinella
51 2.43e-03 ASV_298 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Anaerovorax
53 2.43e-03 ASV_305 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-013
54 2.43e-03 ASV_311 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Moryella
57 2.43e-03 ASV_320 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnoclostridium_10
60 2.43e-03 ASV_348 Bacteria_Firmicutes_Clostridia_Clostridiales_Defluviitaleaceae_Defluviitaleaceae_UCG-011
61 2.43e-03 ASV_357 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinivibrionaceae_UCG-002
62 2.43e-03 ASV_37 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Papillibacter
63 2.43e-03 ASV_376 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_ND3007_group
65 2.43e-03 ASV_399 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcus_2
66 2.43e-03 ASV_4 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_NK4A214_group
68 2.43e-03 ASV_418 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Atopobium
71 2.43e-03 ASV_428 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Marvinbryantia
72 2.43e-03 ASV_429 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetatifactor
73 2.43e-03 ASV_439 Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Mailhella
75 2.43e-03 ASV_450 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Ruminobacter
77 2.43e-03 ASV_457 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-008
78 2.43e-03 ASV_462 Bacteria_Elusimicrobia_Elusimicrobia_Elusimicrobiales_Elusimicrobiaceae_Elusimicrobium
80 2.43e-03 ASV_471 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Solobacterium
81 2.43e-03 ASV_474 Bacteria_Firmicutes_Clostridia_Clostridiales_Family_XIII_Family_XIII_UCG-001
82 2.43e-03 ASV_499 Bacteria_Synergistetes_Synergistia_Synergistales_Synergistaceae_Pyramidobacter
83 2.43e-03 ASV_511 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Succinimonas
84 2.43e-03 ASV_520 Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Nocardiaceae_Rhodococcus
86 2.43e-03 ASV_57 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Blautia
88 2.43e-03 ASV_636 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009
89 2.43e-03 ASV_656 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Coriobacteriales_Incertae_Sedis_Raoultibacter
90 2.43e-03 ASV_66 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Acidaminococcaceae_Succiniclasticum
92 2.43e-03 ASV_670 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Roseburia
94 2.43e-03 ASV_68 Bacteria_Fibrobacteres_Fibrobacteria_Fibrobacterales_Fibrobacteraceae_Fibrobacter
95 2.43e-03 ASV_71 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Butyrivibrio_2
96 2.43e-03 ASV_72 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-001
97 2.43e-03 ASV_733 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004
98 2.43e-03 ASV_793 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-006
99 2.43e-03 ASV_8 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Acetitomaculum
100 2.43e-03 ASV_83 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_9
102 2.43e-03 ASV_90 Bacteria_Actinobacteria_Coriobacteriia_Coriobacteriales_Atopobiaceae_Olsenella
104 2.43e-03 ASV_902 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-002
105 2.43e-03 ASV_91 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_UCG-003
108 2.43e-03 ASV_970 Bacteria_Proteobacteria_Gammaproteobacteria_Aeromonadales_Succinivibrionaceae_Anaerobiospirillum
22 4.59e-03 ASV_16 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_Rikenellaceae_RC9_gut_group
23 4.59e-03 ASV_1658 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Rikenellaceae_U29-B03
28 4.59e-03 ASV_184 Archaea_Euryarchaeota_Methanobacteria_Methanobacteriales_Methanobacteriaceae_Methanosphaera
70 4.59e-03 ASV_4270 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Porphyromonadaceae_Porphyromonas
38 6.56e-03 ASV_2174 Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Variovorax
56 6.56e-03 ASV_3188 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_CAG-352
93 6.56e-03 ASV_674 Bacteria_Firmicutes_Erysipelotrichia_Erysipelotrichales_Erysipelotrichaceae_Catenisphaera
101 6.56e-03 ASV_887 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_NK4A136_group
34 8.25e-03 ASV_212 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-010
74 8.25e-03 ASV_44 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-005
103 8.25e-03 ASV_901 Bacteria_Spirochaetes_Spirochaetia_Spirochaetales_Spirochaetaceae_M2PT2-76_termite_group
106 8.25e-03 ASV_921 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-010
107 8.25e-03 ASV_953 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_FE2018_group
43 1.01e-02 ASV_2300 Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiaceae_1_Clostridium_sensu_stricto_1
67 1.01e-02 ASV_409 Bacteria_Chloroflexi_Anaerolineae_Anaerolineales_Anaerolineaceae_Flexilinea
19 1.16e-02 ASV_149 Bacteria_Proteobacteria_Deltaproteobacteria_Desulfovibrionales_Desulfovibrionaceae_Desulfovibrio
50 1.16e-02 ASV_2617 Bacteria_Bacteroidetes_Bacteroidia_Bacteroidales_Prevotellaceae_Prevotellaceae_YAB2003_group
55 1.16e-02 ASV_3129 Bacteria_Firmicutes_Clostridia_Clostridiales_Syntrophomonadaceae_Pelospora
64 1.16e-02 ASV_3936 Archaea_Euryarchaeota_Thermoplasmata_Methanomassiliicoccales_Methanomethylophilaceae_Candidatus_Methanomethylophilus
14 1.70e-02 ASV_1389 Bacteria_Proteobacteria_Deltaproteobacteria_Desulfuromonadales_Desulfuromonadaceae_Desulfuromonas
24 1.70e-02 ASV_169 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-004
58 2.38e-02 ASV_3273 Bacteria_Actinobacteria_Actinobacteria_Corynebacteriales_Corynebacteriaceae_Corynebacterium
76 2.38e-02 ASV_456 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Veillonellaceae_UCG-001
91 2.38e-02 ASV_669 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Shuttleworthia
37 2.53e-02 ASV_2171 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminococcaceae_UCG-001
36 2.88e-02 ASV_2134 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Coprococcus_2
79 3.19e-02 ASV_4697 Bacteria_Firmicutes_Negativicutes_Selenomonadales_Veillonellaceae_Selenomonas_4
52 4.40e-02 ASV_2981 Bacteria_Firmicutes_Bacilli_Bacillales_Planococcaceae_Planococcus
20 4.52e-02 ASV_1509 Bacteria_Firmicutes_Bacilli_Lactobacillales_Lactobacillaceae_Lactobacillus
35 4.52e-02 ASV_2130 Bacteria_Proteobacteria_Deltaproteobacteria_Desulfobacterales_Desulfobulbaceae_Desulfobulbus
59 4.52e-02 ASV_3393 Bacteria_Firmicutes_Bacilli_Bacillales_Staphylococcaceae_Staphylococcus
69 4.52e-02 ASV_423 Bacteria_Proteobacteria_Gammaproteobacteria_Betaproteobacteriales_Burkholderiaceae_Massilia
87 4.52e-02 ASV_601 Bacteria_Firmicutes_Clostridia_Clostridiales_Lachnospiraceae_Lachnospiraceae_UCG-009
85 4.64e-02 ASV_560 Bacteria_Firmicutes_Clostridia_Clostridiales_Ruminococcaceae_Ruminiclostridium_6

Taking a closer look at the break down of Fibrobacteraceae

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##        Kingdom    Phylum          Class           Order            
## ASV_68 "Bacteria" "Fibrobacteres" "Fibrobacteria" "Fibrobacterales"
##        Family             Genus Species
## ASV_68 "Fibrobacteraceae" NA    NA
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -3.80549    0.13890 -27.397
## Sample_TypeStomach Tube      -1.75544    0.21039  -8.344
## Sample_TypeLiquid Strained   -0.13258    0.12873  -1.030
## Sample_TypeSolid             -0.44736    0.13872  -3.225
## Sample_TypeLiquid Unstrained -0.91152    0.18408  -4.952
## CowIDCow_2477                 0.19984    0.13799   1.448
## CowIDCow_2549                 0.04026    0.14421   0.279
## CowIDCow_796                 -0.07145    0.14797  -0.483
## DayDay_7                     -0.10136    0.13020  -0.778
## DayDay_9                      0.11523    0.11857   0.972
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube             0.00000000011 ***
## Sample_TypeLiquid Strained                0.30854    
## Sample_TypeSolid                          0.00235 ** 
## Sample_TypeLiquid Unstrained        0.00001080133 ***
## CowIDCow_2477                             0.15447    
## CowIDCow_2549                             0.78139    
## CowIDCow_796                              0.63152    
## DayDay_7                                  0.44037    
## DayDay_9                                  0.33635    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.2354     0.2076  -30.03 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -272.44
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -3.64488    0.14105 -25.841
## Sample_TypeStomach Tube      -1.77488    0.21439  -8.279
## Sample_TypeLiquid Strained   -0.10065    0.13002  -0.774
## Sample_TypeSolid             -0.44883    0.14104  -3.182
## Sample_TypeLiquid Unstrained -0.89898    0.18617  -4.829
## CowIDCow_2477                 0.20392    0.13940   1.463
## CowIDCow_2549                 0.03105    0.14606   0.213
## CowIDCow_796                 -0.07921    0.14981  -0.529
## DayDay_7                     -0.09707    0.13200  -0.735
## DayDay_9                      0.12889    0.12009   1.073
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube            0.000000000136 ***
## Sample_TypeLiquid Strained                0.44289    
## Sample_TypeSolid                          0.00265 ** 
## Sample_TypeLiquid Unstrained       0.000016227326 ***
## CowIDCow_2477                             0.15045    
## CowIDCow_2549                             0.83262    
## CowIDCow_796                              0.59961    
## DayDay_7                                  0.46593    
## DayDay_9                                  0.28886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.0413     0.2073  -29.14 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -272.61
## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##         Kingdom    Phylum       Class        Order          
## ASV_103 "Bacteria" "Firmicutes" "Clostridia" "Clostridiales"
##         Family            Genus            Species
## ASV_103 "Ruminococcaceae" "Ruminococcus_1" NA
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value
## (Intercept)                  -3.200533   0.079867 -40.073
## Sample_TypeStomach Tube      -0.767638   0.092303  -8.316
## Sample_TypeLiquid Strained   -0.424786   0.082959  -5.120
## Sample_TypeSolid              0.004558   0.073561   0.062
## Sample_TypeLiquid Unstrained -0.493629   0.094815  -5.206
## CowIDCow_2477                -0.129281   0.079632  -1.623
## CowIDCow_2549                 0.066452   0.076700   0.866
## CowIDCow_796                  0.007782   0.077747   0.100
## DayDay_7                     -0.282765   0.071308  -3.965
## DayDay_9                     -0.111542   0.063832  -1.747
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube             0.00000000012 ***
## Sample_TypeLiquid Strained          0.00000615317 ***
## Sample_TypeSolid                          0.95087    
## Sample_TypeLiquid Unstrained        0.00000461602 ***
## CowIDCow_2477                             0.11147    
## CowIDCow_2549                             0.39088    
## CowIDCow_796                              0.92072    
## DayDay_7                                  0.00026 ***
## DayDay_9                                  0.08738 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -7.0052     0.2308  -30.36 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -268.16

Pulling out the model for Fibrobacteraceae

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##        Kingdom    Phylum          Class           Order            
## ASV_68 "Bacteria" "Fibrobacteres" "Fibrobacteria" "Fibrobacterales"
##        Family             Genus         Species
## ASV_68 "Fibrobacteraceae" "Fibrobacter" NA
## [1] "Model for Fibrobacter"
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -3.64488    0.14105 -25.841
## Sample_TypeStomach Tube      -1.77488    0.21439  -8.279
## Sample_TypeLiquid Strained   -0.10065    0.13002  -0.774
## Sample_TypeSolid             -0.44883    0.14104  -3.182
## Sample_TypeLiquid Unstrained -0.89898    0.18617  -4.829
## CowIDCow_2477                 0.20392    0.13940   1.463
## CowIDCow_2549                 0.03105    0.14606   0.213
## CowIDCow_796                 -0.07921    0.14981  -0.529
## DayDay_7                     -0.09707    0.13200  -0.735
## DayDay_9                      0.12889    0.12009   1.073
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube            0.000000000136 ***
## Sample_TypeLiquid Strained                0.44289    
## Sample_TypeSolid                          0.00265 ** 
## Sample_TypeLiquid Unstrained       0.000016227326 ***
## CowIDCow_2477                             0.15045    
## CowIDCow_2549                             0.83262    
## CowIDCow_796                              0.59961    
## DayDay_7                                  0.46593    
## DayDay_9                                  0.28886    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -6.0413     0.2073  -29.14 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -272.61

Graphing out all the families that are significantly different between grab samples and other rumen sample types.

Pulling out the model for genera in Prevotellaceae here.

## Taxonomy Table:     [7 taxa by 7 taxonomic ranks]:
##          Kingdom    Phylum          Class         Order          
## ASV_91   "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_154  "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_201  "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_72   "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_20   "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_1132 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
## ASV_2617 "Bacteria" "Bacteroidetes" "Bacteroidia" "Bacteroidales"
##          Family           Genus                          Species
## ASV_91   "Prevotellaceae" "Prevotellaceae_UCG-003"       NA     
## ASV_154  "Prevotellaceae" "Prevotellaceae_UCG-004"       NA     
## ASV_201  "Prevotellaceae" "Prevotellaceae_Ga6A1_group"   NA     
## ASV_72   "Prevotellaceae" "Prevotellaceae_UCG-001"       NA     
## ASV_20   "Prevotellaceae" "Prevotella_1"                 NA     
## ASV_1132 "Prevotellaceae" "Prevotellaceae_NK3B31_group"  NA     
## ASV_2617 "Prevotellaceae" "Prevotellaceae_YAB2003_group" NA
## [1] "Model for Prevotella_1"
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -2.75424    0.11121 -24.766
## Sample_TypeStomach Tube       0.22141    0.11474   1.930
## Sample_TypeLiquid Strained    1.25445    0.10022  12.517
## Sample_TypeSolid              0.06410    0.11773   0.544
## Sample_TypeLiquid Unstrained  0.70775    0.11798   5.999
## CowIDCow_2477                 0.09219    0.09069   1.017
## CowIDCow_2549                 0.08058    0.09057   0.890
## CowIDCow_796                 -0.01757    0.09205  -0.191
## DayDay_7                      0.04570    0.08404   0.544
## DayDay_9                      0.11046    0.07559   1.461
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                     0.060 .  
## Sample_TypeLiquid Strained   0.000000000000000293 ***
## Sample_TypeSolid                            0.589    
## Sample_TypeLiquid Unstrained 0.000000313650803771 ***
## CowIDCow_2477                               0.315    
## CowIDCow_2549                               0.378    
## CowIDCow_796                                0.849    
## DayDay_7                                    0.589    
## DayDay_9                                    0.151    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -5.2565     0.1958  -26.84 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -347.35
## [1] "Model for Prevotellaceae_UCG-003"
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                               Estimate Std. Error t value
## (Intercept)                  -4.269117   0.098473 -43.353
## Sample_TypeStomach Tube       0.367820   0.100674   3.654
## Sample_TypeLiquid Strained    1.162644   0.089297  13.020
## Sample_TypeSolid              0.007731   0.107603   0.072
## Sample_TypeLiquid Unstrained  0.885074   0.100617   8.796
## CowIDCow_2477                 0.046630   0.077879   0.599
## CowIDCow_2549                 0.162481   0.076833   2.115
## CowIDCow_796                  0.053311   0.078707   0.677
## DayDay_7                     -0.095193   0.072098  -1.320
## DayDay_9                      0.031053   0.062622   0.496
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                  0.000673 ***
## Sample_TypeLiquid Strained   < 0.0000000000000002 ***
## Sample_TypeSolid                         0.943044    
## Sample_TypeLiquid Unstrained      0.0000000000246 ***
## CowIDCow_2477                            0.552342    
## CowIDCow_2549                            0.040025 *  
## CowIDCow_796                             0.501657    
## DayDay_7                                 0.193406    
## DayDay_9                                 0.622390    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -7.0921     0.2334  -30.39 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -263.07
## [1] "Model for Prevotellaceae_UCG-004"
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -5.47683    0.13755 -39.816
## Sample_TypeStomach Tube      -0.09603    0.12682  -0.757
## Sample_TypeLiquid Strained   -0.69899    0.15142  -4.616
## Sample_TypeSolid              0.30414    0.11276   2.697
## Sample_TypeLiquid Unstrained -0.23747    0.14817  -1.603
## CowIDCow_2477                 0.10932    0.12497   0.875
## CowIDCow_2549                 0.38583    0.11905   3.241
## CowIDCow_796                  0.26012    0.12265   2.121
## DayDay_7                      0.04305    0.10408   0.414
## DayDay_9                      0.02275    0.09893   0.230
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                   0.45285    
## Sample_TypeLiquid Strained              0.0000326 ***
## Sample_TypeSolid                          0.00980 ** 
## Sample_TypeLiquid Unstrained              0.11600    
## CowIDCow_2477                             0.38634    
## CowIDCow_2549                             0.00224 ** 
## CowIDCow_796                              0.03948 *  
## DayDay_7                                  0.68109    
## DayDay_9                                  0.81918    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -8.1820     0.3045  -26.87 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -194.82
## [1] "Model for Prevotellaceae_UCG-001"
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -4.48384    0.09140 -49.060
## Sample_TypeStomach Tube      -0.04059    0.09828  -0.413
## Sample_TypeLiquid Strained    0.84341    0.08280  10.186
## Sample_TypeSolid              0.01873    0.09440   0.198
## Sample_TypeLiquid Unstrained  0.45009    0.09672   4.654
## CowIDCow_2477                -0.12107    0.07433  -1.629
## CowIDCow_2549                -0.12110    0.07549  -1.604
## CowIDCow_796                 -0.16120    0.07646  -2.108
## DayDay_7                      0.01508    0.07125   0.212
## DayDay_9                      0.18122    0.06336   2.860
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                    0.6816    
## Sample_TypeLiquid Strained      0.000000000000291 ***
## Sample_TypeSolid                           0.8436    
## Sample_TypeLiquid Unstrained    0.000028859046887 ***
## CowIDCow_2477                              0.1103    
## CowIDCow_2549                              0.1157    
## CowIDCow_796                               0.0406 *  
## DayDay_7                                   0.8333    
## DayDay_9                                   0.0064 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -7.7963     0.2788  -27.96 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -235.28
## [1] "Model for Prevotellaceae_NK3B31_group"
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -5.87144    0.16744 -35.066
## Sample_TypeStomach Tube      -0.58858    0.19073  -3.086
## Sample_TypeLiquid Strained   -1.08143    0.22449  -4.817
## Sample_TypeSolid              0.25058    0.14697   1.705
## Sample_TypeLiquid Unstrained -0.53659    0.21017  -2.553
## CowIDCow_2477                -0.50695    0.16957  -2.990
## CowIDCow_2549                -0.21946    0.15718  -1.396
## CowIDCow_796                 -0.16570    0.15706  -1.055
## DayDay_7                     -0.09407    0.14453  -0.651
## DayDay_9                     -0.14163    0.13953  -1.015
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                   0.00347 ** 
## Sample_TypeLiquid Strained              0.0000169 ***
## Sample_TypeSolid                          0.09510 .  
## Sample_TypeLiquid Unstrained              0.01414 *  
## CowIDCow_2477                             0.00452 ** 
## CowIDCow_2549                             0.16948    
## CowIDCow_796                              0.29704    
## DayDay_7                                  0.51841    
## DayDay_9                                  0.31552    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)   -8.914      0.470  -18.97 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -151.98

Just looking at methanogens.

Pulling out the model for the ASVs here.

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##         Kingdom   Phylum          Class             Order               
## ASV_184 "Archaea" "Euryarchaeota" "Methanobacteria" "Methanobacteriales"
##         Family                Genus            Species
## ASV_184 "Methanobacteriaceae" "Methanosphaera" NA
## 
## Call:
## bbdml(formula = formula_i, phi.formula = phi.formula, data = data_i, 
##     link = link, phi.link = phi.link, inits = inits)
## 
## 
## Coefficients associated with abundance:
##                              Estimate Std. Error t value
## (Intercept)                  -5.40980    0.18307 -29.551
## Sample_TypeStomach Tube       0.02828    0.17737   0.159
## Sample_TypeLiquid Strained   -0.89032    0.22933  -3.882
## Sample_TypeSolid              0.16642    0.17014   0.978
## Sample_TypeLiquid Unstrained -0.69890    0.25423  -2.749
## CowIDCow_2477                -0.46923    0.17347  -2.705
## CowIDCow_2549                -0.76002    0.19214  -3.956
## CowIDCow_796                 -0.11309    0.16185  -0.699
## DayDay_7                      0.05906    0.15644   0.378
## DayDay_9                     -0.02356    0.15212  -0.155
##                                          Pr(>|t|)    
## (Intercept)                  < 0.0000000000000002 ***
## Sample_TypeStomach Tube                  0.874046    
## Sample_TypeLiquid Strained               0.000336 ***
## Sample_TypeSolid                         0.333253    
## Sample_TypeLiquid Unstrained             0.008573 ** 
## CowIDCow_2477                            0.009610 ** 
## CowIDCow_2549                            0.000268 ***
## CowIDCow_796                             0.488308    
## DayDay_7                                 0.707568    
## DayDay_9                                 0.877614    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Coefficients associated with dispersion:
##             Estimate Std. Error t value            Pr(>|t|)    
## (Intercept)  -7.6642     0.2631  -29.13 <0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## 
## Log-likelihood: -185.92

Checking to see what samples Methanimicrococcus is found in.

## Taxonomy Table:     [1 taxa by 7 taxonomic ranks]:
##          Kingdom   Phylum          Class             Order              
## ASV_5594 "Archaea" "Euryarchaeota" "Methanomicrobia" "Methanosarcinales"
##          Family               Genus                Species
## ASV_5594 "Methanosarcinaceae" "Methanimicrococcus" NA
## [1] Liquid Strained Solid          
## Levels: Liquid Strained Solid
## OTU Table:          [1 taxa and 2 samples]
##                      taxa are rows
##          309 389
## ASV_5594   1   1

Transfaunating what communites?

Based on the analysis above it would see that transfaunation by getting a stomach tube sample would be close to getting a full community into the sick cow. However, if you strain the sample you will bias the communities that your transfaunation gives.

Communites found in stomach tube samples

For this I can think we can just reference the phyla graphs in the “Abundance of Phyla” section. Also we will take a look more specifically at the taxa that the stomach tube samples have in common.

There are 4019 ASVs in Stomach tube samples, but only 255 taxa are present in all stomach tube samples. Due to the variability of stomach tube samples I suspect that with more sampls you will have reduce taxa in common. Stomach tube samples are composed of 20 phyla, 65 orders, 98 families and 236 genera.

Grab vs stomach tube samples

## NULL
## [1] "Families in grab samples not in stomach tube"
##  [1] "Sellimonas"         "Incertae_Sedis"     "Sarcina"           
##  [4] "Rhodobacter"        "Ketogulonicigenium" "Sphingobium"       
##  [7] "Sphingobacterium"   "Rikenella"          "Dyadobacter"       
## [10] "GCA-900066225"      "UBA1819"            "Oscillibacter"
## [1] "Families in stomach tube samples not in grab samples"
##  [1] "Coprococcus_3"                "Lachnospiraceae_NC2004_group"
##  [3] "Cellulosilyticum"             "Clostridioides"              
##  [5] "Filifactor"                   "Parvimonas"                  
##  [7] "Gallicola"                    "Kandleria"                   
##  [9] "Jeotgalibaca"                 "Aeribacillus"                
## [11] "Cellvibrio"                   "Alysiella"                   
## [13] "Xylophilus"                   "Verticia"                    
## [15] "Oligella"                     "Moraxella"                   
## [17] "Caviibacter"                  "Bilophila"                   
## [19] "Bifidobacterium"              "Rathayibacter"               
## [21] "Curtobacterium"               "Clavibacter"                 
## [23] "Leucobacter"                  "Kocuria"                     
## [25] "Parvibacter"                  "Harryflintia"                
## [27] "Fournierella"                 "Oscillospira"
##  [1] "Sellimonas"         "Incertae_Sedis"     "Sarcina"           
##  [4] "Rhodobacter"        "Ketogulonicigenium" "Sphingobium"       
##  [7] "Sphingobacterium"   "Rikenella"          "Dyadobacter"       
## [10] "GCA-900066225"      "UBA1819"            "Oscillibacter"

These the 12 genera found in the grab sample, but not the stomach tube.

##  [1] "Lachnospiraceae"                 "Defluviitaleaceae"              
##  [3] NA                                "Ruminococcaceae"                
##  [5] "Veillonellaceae"                 "Peptostreptococcaceae"          
##  [7] "Family_XIII"                     "Family_XI"                      
##  [9] "Clostridiales_vadinBB60_group"   "Anaeroplasmataceae"             
## [11] "Erysipelotrichaceae"             "Mycoplasmataceae"               
## [13] "Streptococcaceae"                "Leuconostocaceae"               
## [15] "Lactobacillaceae"                "Enterococcaceae"                
## [17] "Carnobacteriaceae"               "Aerococcaceae"                  
## [19] "Staphylococcaceae"               "Planococcaceae"                 
## [21] "Bacillaceae"                     "Peptococcaceae"                 
## [23] "Christensenellaceae"             "Clostridiaceae_1"               
## [25] "Acidaminococcaceae"              "Syntrophomonadaceae"            
## [27] "Eubacteriaceae"                  "Puniceicoccaceae"               
## [29] "Pedosphaeraceae"                 "Akkermansiaceae"                
## [31] "Campylobacteraceae"              "Elusimicrobiaceae"              
## [33] "Pirellulaceae"                   "Saccharimonadaceae"             
## [35] "Endomicrobiaceae"                "Xanthomonadaceae"               
## [37] "Pseudomonadaceae"                "Succinivibrionaceae"            
## [39] "Enterobacteriaceae"              "Burkholderiaceae"               
## [41] "Cardiobacteriaceae"              "Pasteurellaceae"                
## [43] "Moraxellaceae"                   "Desulfobulbaceae"               
## [45] "Oligoflexaceae"                  "Paracaedibacteraceae"           
## [47] "Leptotrichiaceae"                "Fusobacteriaceae"               
## [49] "Methanobacteriaceae"             "Methanomethylophilaceae"        
## [51] "Methanocorpusculaceae"           "Devosiaceae"                    
## [53] "Sphingomonadaceae"               "Rhizobiaceae"                   
## [55] "Beijerinckiaceae"                "Caulobacteraceae"               
## [57] "Desulfovibrionaceae"             "Desulfuromonadaceae"            
## [59] "Spirochaetaceae"                 "vadinBE97"                      
## [61] "Victivallaceae"                  "Beutenbergiaceae"               
## [63] "Microbacteriaceae"               "Sanguibacteraceae"              
## [65] "Corynebacteriaceae"              "Nocardiaceae"                   
## [67] "Nocardioidaceae"                 "Coriobacteriales_Incertae_Sedis"
## [69] "Eggerthellaceae"                 "Atopobiaceae"                   
## [71] "Fibrobacteraceae"                "Anaerolineaceae"                
## [73] "0319-6G20"                       "Synergistaceae"                 
## [75] "Prevotellaceae"                  "Bacteroidales_UCG-001"          
## [77] "Bacteroidaceae"                  "p-251-o5"                       
## [79] "Muribaculaceae"                  "Marinifilaceae"                 
## [81] "F082"                            "Rikenellaceae"                  
## [83] "Bacteroidetes_BD2-2"             "Sphingobacteriaceae"            
## [85] "PeH15"                           "M2PB4-65_termite_group"         
## [87] "Bacteroidales_BS11_gut_group"    "COB_P4-1_termite_group"         
## [89] "Marinilabiliaceae"               "Tannerellaceae"                 
## [91] "Paludibacteraceae"               "Porphyromonadaceae"             
## [93] "Bacteroidales_RF16_group"
##   [1] "Lachnospiraceae_AC2044_group"                      
##   [2] NA                                                  
##   [3] "Lachnospiraceae_NK4A136_group"                     
##   [4] "Lachnospiraceae_FE2018_group"                      
##   [5] "Lachnospiraceae_ND3007_group"                      
##   [6] "Acetatifactor"                                     
##   [7] "Acetitomaculum"                                    
##   [8] "Oribacterium"                                      
##   [9] "Howardella"                                        
##  [10] "Lachnospiraceae_UCG-009"                           
##  [11] "Dorea"                                             
##  [12] "Marvinbryantia"                                    
##  [13] "Lachnoclostridium_10"                              
##  [14] "Fusicatenibacter"                                  
##  [15] "Blautia"                                           
##  [16] "Lachnospiraceae_NK3A20_group"                      
##  [17] "Lachnospiraceae_XPB1014_group"                     
##  [18] "Lachnospiraceae_UCG-006"                           
##  [19] "XBB1006"                                           
##  [20] "Roseburia"                                         
##  [21] "Shuttleworthia"                                    
##  [22] "Lachnoclostridium"                                 
##  [23] "FD2005"                                            
##  [24] "Agathobacter"                                      
##  [25] "Lachnospiraceae_UCG-001"                           
##  [26] "Pseudobutyrivibrio"                                
##  [27] "Tyzzerella_4"                                      
##  [28] "Moryella"                                          
##  [29] "Lachnospiraceae_UCG-002"                           
##  [30] "Syntrophococcus"                                   
##  [31] "Butyrivibrio_2"                                    
##  [32] "Lachnoclostridium_1"                               
##  [33] "Butyrivibrio"                                      
##  [34] "Anaerosporobacter"                                 
##  [35] "Lachnoclostridium_12"                              
##  [36] "Lachnospira"                                       
##  [37] "Lachnospiraceae_FCS020_group"                      
##  [38] "Lachnospiraceae_UCG-008"                           
##  [39] "Lachnospiraceae_NK4B4_group"                       
##  [40] "Coprococcus_2"                                     
##  [41] "Defluviitaleaceae_UCG-011"                         
##  [42] "Lachnospiraceae_UCG-010"                           
##  [43] "Tyzzerella"                                        
##  [44] "Coprococcus_1"                                     
##  [45] "GCA-900066575"                                     
##  [46] "Ruminococcaceae_UCG-014"                           
##  [47] "Tyzzerella_3"                                      
##  [48] "Candidatus_Soleaferrea"                            
##  [49] "Megasphaera"                                       
##  [50] "Veillonellaceae_UCG-001"                           
##  [51] "Quinella"                                          
##  [52] "Selenomonas_1"                                     
##  [53] "Schwartzia"                                        
##  [54] "Selenomonas_4"                                     
##  [55] "Anaerovibrio"                                      
##  [56] "Romboutsia"                                        
##  [57] "Family_XIII_AD3011_group"                          
##  [58] "Mogibacterium"                                     
##  [59] "Anaerovorax"                                       
##  [60] "Family_XIII_UCG-001"                               
##  [61] "Murdochiella"                                      
##  [62] "Helcococcus"                                       
##  [63] "Peptoniphilus"                                     
##  [64] "Anaeroplasma"                                      
##  [65] "Catenisphaera"                                     
##  [66] "Erysipelotrichaceae_UCG-006"                       
##  [67] "Solobacterium"                                     
##  [68] "Erysipelotrichaceae_UCG-009"                       
##  [69] "Erysipelotrichaceae_UCG-008"                       
##  [70] "Erysipelotrichaceae_UCG-004"                       
##  [71] "Erysipelatoclostridium"                            
##  [72] "Mycoplasma"                                        
##  [73] "Streptococcus"                                     
##  [74] "Weissella"                                         
##  [75] "Lactobacillus"                                     
##  [76] "Enterococcus"                                      
##  [77] "Desemzia"                                          
##  [78] "Aerococcus"                                        
##  [79] "Turicibacter"                                      
##  [80] "Staphylococcus"                                    
##  [81] "Planococcus"                                       
##  [82] "Clostridium_sensu_stricto_1"                       
##  [83] "Phascolarctobacterium"                             
##  [84] "Succiniclasticum"                                  
##  [85] "Pelospora"                                         
##  [86] "Eubacterium"                                       
##  [87] "Anaerofustis"                                      
##  [88] "Akkermansia"                                       
##  [89] "Campylobacter"                                     
##  [90] "Elusimicrobium"                                    
##  [91] "p-1088-a5_gut_group"                               
##  [92] "Pirellula"                                         
##  [93] "CPla-4_termite_group"                              
##  [94] "Candidatus_Saccharimonas"                          
##  [95] "Candidatus_Endomicrobium"                          
##  [96] "Thermomonas"                                       
##  [97] "Stenotrophomonas"                                  
##  [98] "Pseudomonas"                                       
##  [99] "Succinimonas"                                      
## [100] "Anaerobiospirillum"                                
## [101] "Succinivibrio"                                     
## [102] "Pantoea"                                           
## [103] "Klebsiella"                                        
## [104] "Sutterella"                                        
## [105] "Variovorax"                                        
## [106] "Limnohabitans"                                     
## [107] "Comamonas"                                         
## [108] "Janthinobacterium"                                 
## [109] "Massilia"                                          
## [110] "Duganella"                                         
## [111] "Suttonella"                                        
## [112] "Bibersteinia"                                      
## [113] "Actinobacillus"                                    
## [114] "Escherichia/Shigella"                              
## [115] "Ruminobacter"                                      
## [116] "Psychrobacter"                                     
## [117] "Acinetobacter"                                     
## [118] "Succinivibrionaceae_UCG-002"                       
## [119] "Desulfobulbus"                                     
## [120] "Leptotrichia"                                      
## [121] "Fusobacterium"                                     
## [122] "Methanobrevibacter"                                
## [123] "Methanosphaera"                                    
## [124] "Candidatus_Methanomethylophilus"                   
## [125] "Methanocorpusculum"                                
## [126] "Devosia"                                           
## [127] "Sphingomonas"                                      
## [128] "Novosphingobium"                                   
## [129] "Ochrobactrum"                                      
## [130] "Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium"
## [131] "Neorhizobium"                                      
## [132] "Chelativorans"                                     
## [133] "Methylobacterium"                                  
## [134] "Brevundimonas"                                     
## [135] "Desulfovibrio"                                     
## [136] "Mailhella"                                         
## [137] "Desulfuromonas"                                    
## [138] "M2PT2-76_termite_group"                            
## [139] "Sediminispirochaeta"                               
## [140] "Treponema_2"                                       
## [141] "Salana"                                            
## [142] "Pseudoclavibacter"                                 
## [143] "Galbitalea"                                        
## [144] "Frigoribacterium"                                  
## [145] "Sanguibacter"                                      
## [146] "Corynebacterium_1"                                 
## [147] "Corynebacterium"                                   
## [148] "Rhodococcus"                                       
## [149] "Aeromicrobium"                                     
## [150] "Raoultibacter"                                     
## [151] "Denitrobacterium"                                  
## [152] "DNF00809"                                          
## [153] "Slackia"                                           
## [154] "Atopobium"                                         
## [155] "Olsenella"                                         
## [156] "Fibrobacter"                                       
## [157] "Flexilinea"                                        
## [158] "Synergistes"                                       
## [159] "Fretibacterium"                                    
## [160] "Pyramidobacter"                                    
## [161] "Christensenellaceae_R-7_group"                     
## [162] "Ruminococcaceae_UCG-010"                           
## [163] "Prevotellaceae_UCG-003"                            
## [164] "Alloprevotella"                                    
## [165] "Prevotellaceae_UCG-004"                            
## [166] "Prevotellaceae_UCG-001"                            
## [167] "Prevotellaceae_Ga6A1_group"                        
## [168] "Prevotella_1"                                      
## [169] "Prevotellaceae_NK3B31_group"                       
## [170] "Prevotellaceae_YAB2003_group"                      
## [171] "Bacteroides"                                       
## [172] "Rikenellaceae_RC9_gut_group"                       
## [173] "dgA-11_gut_group"                                  
## [174] "U29-B03"                                           
## [175] "Pedobacter"                                        
## [176] "Alistipes"                                         
## [177] "Tannerella"                                        
## [178] "Parabacteroides"                                   
## [179] "Porphyromonas"                                     
## [180] "hoa5-07d05_gut_group"                              
## [181] "Ruminiclostridium_6"                               
## [182] "Ruminococcus_1"                                    
## [183] "Angelakisella"                                     
## [184] "Ruminiclostridium"                                 
## [185] "Hydrogenoanaerobacterium"                          
## [186] "Subdoligranulum"                                   
## [187] "Caproiciproducens"                                 
## [188] "Ruminococcus_2"                                    
## [189] "Ruminococcaceae_UCG-001"                           
## [190] "Ruminiclostridium_5"                               
## [191] "CAG-352"                                           
## [192] "Saccharofermentans"                                
## [193] "Ruminiclostridium_1"                               
## [194] "Ruminococcaceae_UCG-012"                           
## [195] "Ruminococcaceae_UCG-013"                           
## [196] "Ruminococcaceae_UCG-009"                           
## [197] "Ruminococcaceae_NK4A214_group"                     
## [198] "Papillibacter"                                     
## [199] "Ruminococcaceae_UCG-007"                           
## [200] "Ruminococcaceae_V9D2013_group"                     
## [201] "Sporobacter"                                       
## [202] "Ruminococcaceae_UCG-005"                           
## [203] "Ruminococcaceae_UCG-004"                           
## [204] "Ruminococcaceae_UCG-002"                           
## [205] "Ruminiclostridium_9"                               
## [206] "Flavonifractor"                                    
## [207] "possible_genus_Sk018"                              
## [208] "probable_genus_10"

These are the 208 genera that are found in both the grab sample and stomach tube.

There are 255 ASVs are found in the grab samples, but not found in the stomach tube samples and 404 are found in the stomach tube samples, but not found in the grab samples. There is also 3615 ASVs found in common between grab samples and stomach tube samples. Let’s check at a higher taxonomic rank next.

Let’s compare the stomach tube samples to the “gold standard” of grab sample.

There are 199 ASVs and 43 genera and 13 significant differentially abundant between stomach tube and grab samples.

Unique Genera that are significant differentially abundant
x
Firmicutes_Lachnospiraceae_Lachnospiraceae_ND3007_group
Firmicutes_Lachnospiraceae_Lachnospiraceae_NK4A136_group
Firmicutes_Lachnospiraceae_Acetatifactor
Firmicutes_Lachnospiraceae_Oribacterium
Firmicutes_Lachnospiraceae_Howardella
Firmicutes_Lachnospiraceae_Blautia
Firmicutes_Lachnospiraceae_XBB1006
Firmicutes_Lachnospiraceae_Shuttleworthia
Firmicutes_Lachnospiraceae_Pseudobutyrivibrio
Firmicutes_Lachnospiraceae_Lachnospiraceae_AC2044_group_bacterium
Firmicutes_Lachnospiraceae_Butyrivibrio_2
Firmicutes_Lachnospiraceae_Acetitomaculum
Firmicutes_Lachnospiraceae_Lachnoclostridium_10
Firmicutes_Lachnospiraceae_Coprococcus_2
Firmicutes_Lachnospiraceae_Lachnospiraceae_FCS020_group_bacterium
Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-014
Firmicutes_Family_XIII_Mogibacterium
Firmicutes_Erysipelotrichaceae_Catenisphaera
Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-009
Firmicutes_Erysipelotrichaceae_Erysipelotrichaceae_UCG-004
Firmicutes_Streptococcaceae_Streptococcus
Firmicutes_Lactobacillaceae_Lactobacillus
Proteobacteria_Cardiobacteriaceae_Suttonella
Euryarchaeota_Methanobacteriaceae_Methanobrevibacter
Spirochaetes_Spirochaetaceae_Sediminispirochaeta
Actinobacteria_Atopobiaceae_Olsenella
Fibrobacteres_Fibrobacteraceae_Fibrobacter_succinogenes
Bacteroidetes_Prevotellaceae_Prevotellaceae_UCG-003
Bacteroidetes_Prevotellaceae_Prevotellaceae_Ga6A1_group
Bacteroidetes_Prevotellaceae_Prevotellaceae_NK3B31_group
Firmicutes_Ruminococcaceae_Ruminococcus_1
Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-001
Firmicutes_Ruminococcaceae_Ruminococcus_2
Firmicutes_Ruminococcaceae_CAG-352
Firmicutes_Ruminococcaceae_Saccharofermentans
Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-013
Firmicutes_Ruminococcaceae_Ruminococcaceae_NK4A214_group
Firmicutes_Ruminococcaceae_Ruminiclostridium_9
Firmicutes_Ruminococcaceae_Ruminococcaceae_V9D2013_group
Firmicutes_Ruminococcaceae_Ruminococcaceae_UCG-004
Firmicutes_Lachnospiraceae_Lachnospiraceae_XPB1014_group
Firmicutes_Lachnospiraceae_possible_genus_Sk018
Firmicutes_Lachnospiraceae_probable_genus_10

These are the the unique genera that are significant differentially abundant between grab and stomach tube samples.

# of significant genera in each family
Var1 Freq
Firmicutes_Lachnospiraceae 54
Firmicutes_Ruminococcaceae 31
Bacteroidetes_Prevotellaceae 25
Firmicutes_Christensenellaceae 17
Fibrobacteres_Fibrobacteraceae 16
Bacteroidetes_Rikenellaceae 8
Spirochaetes_Spirochaetaceae 8
Euryarchaeota_Methanobacteriaceae 4
Firmicutes_Erysipelotrichaceae 4
Kiritimatiellaeota 4
Lentisphaerae_vadinBE97 4
Bacteroidetes_F082 3
Firmicutes_Family_XIII 3
Actinobacteria_Atopobiaceae 2
Bacteroidetes_Bacteroidales_BS11_gut_group 2
Actinobacteria_Eggerthellaceae 1
Bacteroidetes 1
Bacteroidetes_Bacteroidales_RF16_group 1
Bacteroidetes_Bacteroidetes_BD2-2 1
Bacteroidetes_Muribaculaceae 1
Bacteroidetes_p-251-o5 1
Cyanobacteria 1
Euryarchaeota_Methanomethylophilaceae 1
Firmicutes_Streptococcaceae 1
Patescibacteria 1
Proteobacteria_Burkholderiaceae 1
Proteobacteria_Succinivibrionaceae 1
Tenericutes 1
Verrucomicrobia 1

From this we can see that Lachnospiraceae, Ruminococcaceae, Prevotellaceae and Erysipelotrichaceae were the most common families to have significant differentially abundant ASVs in grab vs stomach tube samples. We will take a closer look at all ASVs differentially abundant.

## 
## -1  1 
## 21 10

This is the number of ASVs in the family Lachnospiraceae that are positively and negatively associated in stomach tube samples.

## 
## -1  1 
## 15  3
x Family Genus
7 -1.3060006 Lachnospiraceae XBB1006
3 -1.2804052 Lachnospiraceae Acetatifactor
13 -1.0189351 Lachnospiraceae Lachnoclostridium_10
14 -0.9426866 Lachnospiraceae Coprococcus_2
15 -0.9321014 Lachnospiraceae Lachnospiraceae_FCS020_group
18 -0.9037477 Lachnospiraceae probable_genus_10
1 -0.8064012 Lachnospiraceae Lachnospiraceae_ND3007_group
8 -0.7601064 Lachnospiraceae Shuttleworthia
10 -0.7250690 Lachnospiraceae Lachnospiraceae_AC2044_group
2 -0.6223167 Lachnospiraceae Lachnospiraceae_NK4A136_group
9 -0.5251488 Lachnospiraceae Pseudobutyrivibrio
17 -0.4515620 Lachnospiraceae possible_genus_Sk018
11 -0.2900656 Lachnospiraceae Butyrivibrio_2
16 -0.2899893 Lachnospiraceae Lachnospiraceae_XPB1014_group
4 -0.2788123 Lachnospiraceae Oribacterium
6 0.3521225 Lachnospiraceae Blautia
12 0.3915896 Lachnospiraceae Acetitomaculum
5 1.8266653 Lachnospiraceae Howardella

Going to check if there are an Euryarchaeota that are only found in one sample type.

## Taxonomy Table:     [32 taxa by 7 taxonomic ranks]:
##          Kingdom   Phylum          Class            
## ASV_1308 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1441 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4053 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_5508 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_7    "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_184  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3038 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3184 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_264  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_710  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4546 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_4863 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_24   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1749 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_88   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1703 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_84   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1323 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_484  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_599  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3860 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_1114 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_948  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_700  "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3066 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_54   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_5586 "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_58   "Archaea" "Euryarchaeota" "Methanobacteria"
## ASV_3936 "Archaea" "Euryarchaeota" "Thermoplasmata" 
## ASV_5594 "Archaea" "Euryarchaeota" "Methanomicrobia"
## ASV_1434 "Archaea" "Euryarchaeota" "Methanomicrobia"
## ASV_4298 "Archaea" "Euryarchaeota" "Methanomicrobia"
##          Order                     Family                   
## ASV_1308 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1441 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_4053 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_5508 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_7    "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_184  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3038 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3184 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_264  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_710  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_4546 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_4863 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_24   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1749 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_88   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1703 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_84   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1323 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_484  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_599  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3860 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_1114 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_948  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_700  "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3066 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_54   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_5586 "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_58   "Methanobacteriales"      "Methanobacteriaceae"    
## ASV_3936 "Methanomassiliicoccales" "Methanomethylophilaceae"
## ASV_5594 "Methanosarcinales"       "Methanosarcinaceae"     
## ASV_1434 "Methanomicrobiales"      "Methanocorpusculaceae"  
## ASV_4298 "Methanomicrobiales"      "Methanocorpusculaceae"  
##          Genus                             Species
## ASV_1308 "Methanobrevibacter"              NA     
## ASV_1441 "Methanobrevibacter"              NA     
## ASV_4053 "Methanobrevibacter"              NA     
## ASV_5508 "Methanobrevibacter"              NA     
## ASV_7    "Methanobrevibacter"              NA     
## ASV_184  "Methanosphaera"                  NA     
## ASV_3038 "Methanosphaera"                  NA     
## ASV_3184 "Methanosphaera"                  NA     
## ASV_264  "Methanosphaera"                  NA     
## ASV_710  "Methanosphaera"                  NA     
## ASV_4546 "Methanobrevibacter"              NA     
## ASV_4863 "Methanobrevibacter"              NA     
## ASV_24   "Methanobrevibacter"              NA     
## ASV_1749 "Methanobrevibacter"              NA     
## ASV_88   "Methanobrevibacter"              NA     
## ASV_1703 "Methanobrevibacter"              NA     
## ASV_84   "Methanobrevibacter"              NA     
## ASV_1323 "Methanobrevibacter"              NA     
## ASV_484  "Methanobrevibacter"              NA     
## ASV_599  "Methanobrevibacter"              NA     
## ASV_3860 "Methanobrevibacter"              NA     
## ASV_1114 "Methanobrevibacter"              NA     
## ASV_948  "Methanobrevibacter"              NA     
## ASV_700  "Methanobrevibacter"              NA     
## ASV_3066 "Methanobrevibacter"              NA     
## ASV_54   "Methanobrevibacter"              NA     
## ASV_5586 "Methanobrevibacter"              NA     
## ASV_58   "Methanobrevibacter"              NA     
## ASV_3936 "Candidatus_Methanomethylophilus" NA     
## ASV_5594 "Methanimicrococcus"              NA     
## ASV_1434 "Methanocorpusculum"              NA     
## ASV_4298 "Methanocorpusculum"              NA
##  [1] Stomach Tube      Stomach Tube      Stomach Tube     
##  [4] Stomach Tube      Stomach Tube      Stomach Tube     
##  [7] Stomach Tube      Stomach Tube      Stomach Tube     
## [10] Stomach Tube      Stomach Tube      Grab Sample      
## [13] Grab Sample       Grab Sample       Grab Sample      
## [16] Grab Sample       Grab Sample       Grab Sample      
## [19] Grab Sample       Grab Sample       Grab Sample      
## [22] Grab Sample       Grab Sample       Liquid Strained  
## [25] Liquid Strained   Liquid Strained   Liquid Strained  
## [28] Liquid Strained   Liquid Strained   Liquid Strained  
## [31] Stomach Tube      Liquid Unstrained Liquid Unstrained
## [34] Liquid Unstrained Liquid Unstrained Liquid Unstrained
## [37] Liquid Unstrained Feces             Feces            
## [40] Feces             Solid             Solid            
## [43] Solid             Solid             Solid            
## [46] Solid             Solid             Solid            
## [49] Solid             Solid             Solid            
## [52] Solid             Liquid Strained   Liquid Strained  
## [55] Liquid Strained   Liquid Strained   Liquid Strained  
## [58] Liquid Unstrained Liquid Unstrained
## 6 Levels: Grab Sample Feces Stomach Tube Liquid Strained ... Liquid Unstrained
## OTU Table:          [1 taxa and 59 samples]
##                      taxa are rows
##         282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
## ASV_231  18  30  10  12  16   4  11   6  12   9  13  17   6   4   9  10
##         298 299 300 301 302 303 304 306 307 308 309 310 311 312 314 359
## ASV_231   8  16  16  10   6  11   6  14   6   7  30  23  22   5  10  12
##         360 361 362 363 365 368 371 373 379 380 381 382 383 384 385 386
## ASV_231  17  17  14   8  19   2   1   1  25  38  15  45  18  24  15  53
##         387 388 389 390 505 506 507 508 509 510 511
## ASV_231  38  23  34   6   9  19   8   2  63  42  35

These are the genera that are significant differentially abundant genera in stomach tube vs grab samples.

## [1] NA            "Fibrobacter"

The only assigned genera in the family Fibrobacteraceae, Fibrobacter was significantly lower in abundance in stomach tubes compared to grab samples.

x Phylum Family Genus
-1.8769355 Fibrobacteres Fibrobacteraceae Fibrobacter
-1.3060006 Firmicutes Lachnospiraceae XBB1006
-1.2804052 Firmicutes Lachnospiraceae Acetatifactor
-1.0189351 Firmicutes Lachnospiraceae Lachnoclostridium_10
-0.9426866 Firmicutes Lachnospiraceae Coprococcus_2
-0.9321014 Firmicutes Lachnospiraceae Lachnospiraceae_FCS020_group
-0.9037477 Firmicutes Lachnospiraceae probable_genus_10
-0.8739379 Bacteroidetes Prevotellaceae Prevotellaceae_Ga6A1_group
-0.8064012 Firmicutes Lachnospiraceae Lachnospiraceae_ND3007_group
-0.7661424 Firmicutes Ruminococcaceae Ruminococcus_1
-0.7601064 Firmicutes Lachnospiraceae Shuttleworthia
-0.7250690 Firmicutes Lachnospiraceae Lachnospiraceae_AC2044_group
-0.7159013 Spirochaetes Spirochaetaceae Sediminispirochaeta
-0.6223167 Firmicutes Lachnospiraceae Lachnospiraceae_NK4A136_group
-0.5577767 Bacteroidetes Prevotellaceae Prevotellaceae_NK3B31_group
-0.5251488 Firmicutes Lachnospiraceae Pseudobutyrivibrio
-0.4677556 Firmicutes Ruminococcaceae Saccharofermentans
-0.4515620 Firmicutes Lachnospiraceae possible_genus_Sk018
-0.3024765 Firmicutes Ruminococcaceae Ruminococcaceae_UCG-014
-0.2900656 Firmicutes Lachnospiraceae Butyrivibrio_2
-0.2899893 Firmicutes Lachnospiraceae Lachnospiraceae_XPB1014_group
-0.2788123 Firmicutes Lachnospiraceae Oribacterium
0.3193401 Euryarchaeota Methanobacteriaceae Methanobrevibacter
0.3521225 Firmicutes Lachnospiraceae Blautia
0.3735289 Firmicutes Family_XIII Mogibacterium
0.3767681 Bacteroidetes Prevotellaceae Prevotellaceae_UCG-003
0.3915896 Firmicutes Lachnospiraceae Acetitomaculum
0.4050196 Firmicutes Ruminococcaceae Ruminococcaceae_NK4A214_group
0.4068741 Firmicutes Ruminococcaceae Ruminococcaceae_UCG-004
0.4091719 Firmicutes Ruminococcaceae Ruminococcus_2
0.4213922 Firmicutes Ruminococcaceae Ruminococcaceae_V9D2013_group
0.6291728 Firmicutes Erysipelotrichaceae Catenisphaera
0.7125459 Firmicutes Ruminococcaceae Ruminococcaceae_UCG-001
0.7537462 Actinobacteria Atopobiaceae Olsenella
0.7998338 Firmicutes Lactobacillaceae Lactobacillus
0.9805989 Firmicutes Erysipelotrichaceae Erysipelotrichaceae_UCG-009
1.0394506 Firmicutes Ruminococcaceae Ruminococcaceae_UCG-013
1.1037244 Firmicutes Ruminococcaceae Ruminiclostridium_9
1.1678026 Firmicutes Erysipelotrichaceae Erysipelotrichaceae_UCG-004
1.5268279 Firmicutes Ruminococcaceae CAG-352
1.6367580 Proteobacteria Cardiobacteriaceae Suttonella
1.8266653 Firmicutes Lachnospiraceae Howardella
1.8417467 Firmicutes Streptococcaceae Streptococcus

Grab vs liquid strained samples

Let’s compare the liquid strained samples to the “gold standard” of grab sample.

There are 283 ASVs are found in the grab sample, but not found in the liquid strained samples. There is also 3587 ASVs found in common between grab samples. Thus, stomach tube samples tend to be more like a grab sample than a strained sample. Let’s check at a higher taxonomic rank next.

## [1] "Sellimonas"               "Tyzzerella"              
## [3] "Desemzia"                 "Limnohabitans"           
## [5] "Leptotrichia"             "Salana"                  
## [7] "Rikenella"                "GCA-900066225"           
## [9] "Hydrogenoanaerobacterium"

These genera are found in the grab sample, but not the stomach tube.

##   [1] "Lachnospiraceae_AC2044_group"                      
##   [2] NA                                                  
##   [3] "Lachnospiraceae_NK4A136_group"                     
##   [4] "Lachnospiraceae_FE2018_group"                      
##   [5] "Lachnospiraceae_ND3007_group"                      
##   [6] "Acetatifactor"                                     
##   [7] "Acetitomaculum"                                    
##   [8] "Oribacterium"                                      
##   [9] "Howardella"                                        
##  [10] "Lachnospiraceae_UCG-009"                           
##  [11] "Dorea"                                             
##  [12] "Marvinbryantia"                                    
##  [13] "Lachnoclostridium_10"                              
##  [14] "Fusicatenibacter"                                  
##  [15] "Blautia"                                           
##  [16] "Lachnospiraceae_NK3A20_group"                      
##  [17] "Lachnospiraceae_XPB1014_group"                     
##  [18] "Lachnospiraceae_UCG-006"                           
##  [19] "XBB1006"                                           
##  [20] "Roseburia"                                         
##  [21] "Shuttleworthia"                                    
##  [22] "Lachnoclostridium"                                 
##  [23] "FD2005"                                            
##  [24] "Agathobacter"                                      
##  [25] "Lachnospiraceae_UCG-001"                           
##  [26] "Pseudobutyrivibrio"                                
##  [27] "Tyzzerella_4"                                      
##  [28] "Moryella"                                          
##  [29] "Lachnospiraceae_UCG-002"                           
##  [30] "Syntrophococcus"                                   
##  [31] "Butyrivibrio_2"                                    
##  [32] "Lachnoclostridium_1"                               
##  [33] "Butyrivibrio"                                      
##  [34] "Anaerosporobacter"                                 
##  [35] "Lachnoclostridium_12"                              
##  [36] "Lachnospira"                                       
##  [37] "Lachnospiraceae_FCS020_group"                      
##  [38] "Lachnospiraceae_UCG-008"                           
##  [39] "Lachnospiraceae_NK4B4_group"                       
##  [40] "Coprococcus_2"                                     
##  [41] "Defluviitaleaceae_UCG-011"                         
##  [42] "Lachnospiraceae_UCG-010"                           
##  [43] "Coprococcus_1"                                     
##  [44] "GCA-900066575"                                     
##  [45] "Incertae_Sedis"                                    
##  [46] "Ruminococcaceae_UCG-014"                           
##  [47] "Tyzzerella_3"                                      
##  [48] "Candidatus_Soleaferrea"                            
##  [49] "Megasphaera"                                       
##  [50] "Veillonellaceae_UCG-001"                           
##  [51] "Quinella"                                          
##  [52] "Selenomonas_1"                                     
##  [53] "Schwartzia"                                        
##  [54] "Selenomonas_4"                                     
##  [55] "Anaerovibrio"                                      
##  [56] "Romboutsia"                                        
##  [57] "Family_XIII_AD3011_group"                          
##  [58] "Mogibacterium"                                     
##  [59] "Anaerovorax"                                       
##  [60] "Family_XIII_UCG-001"                               
##  [61] "Murdochiella"                                      
##  [62] "Helcococcus"                                       
##  [63] "Peptoniphilus"                                     
##  [64] "Anaeroplasma"                                      
##  [65] "Catenisphaera"                                     
##  [66] "Erysipelotrichaceae_UCG-006"                       
##  [67] "Solobacterium"                                     
##  [68] "Erysipelotrichaceae_UCG-009"                       
##  [69] "Erysipelotrichaceae_UCG-008"                       
##  [70] "Erysipelotrichaceae_UCG-004"                       
##  [71] "Erysipelatoclostridium"                            
##  [72] "Mycoplasma"                                        
##  [73] "Streptococcus"                                     
##  [74] "Weissella"                                         
##  [75] "Lactobacillus"                                     
##  [76] "Enterococcus"                                      
##  [77] "Aerococcus"                                        
##  [78] "Turicibacter"                                      
##  [79] "Staphylococcus"                                    
##  [80] "Planococcus"                                       
##  [81] "Clostridium_sensu_stricto_1"                       
##  [82] "Sarcina"                                           
##  [83] "Phascolarctobacterium"                             
##  [84] "Succiniclasticum"                                  
##  [85] "Pelospora"                                         
##  [86] "Eubacterium"                                       
##  [87] "Anaerofustis"                                      
##  [88] "Akkermansia"                                       
##  [89] "Campylobacter"                                     
##  [90] "Elusimicrobium"                                    
##  [91] "p-1088-a5_gut_group"                               
##  [92] "Pirellula"                                         
##  [93] "CPla-4_termite_group"                              
##  [94] "Candidatus_Saccharimonas"                          
##  [95] "Candidatus_Endomicrobium"                          
##  [96] "Thermomonas"                                       
##  [97] "Stenotrophomonas"                                  
##  [98] "Pseudomonas"                                       
##  [99] "Succinimonas"                                      
## [100] "Anaerobiospirillum"                                
## [101] "Succinivibrio"                                     
## [102] "Pantoea"                                           
## [103] "Klebsiella"                                        
## [104] "Sutterella"                                        
## [105] "Variovorax"                                        
## [106] "Comamonas"                                         
## [107] "Janthinobacterium"                                 
## [108] "Massilia"                                          
## [109] "Duganella"                                         
## [110] "Suttonella"                                        
## [111] "Bibersteinia"                                      
## [112] "Actinobacillus"                                    
## [113] "Escherichia/Shigella"                              
## [114] "Ruminobacter"                                      
## [115] "Psychrobacter"                                     
## [116] "Acinetobacter"                                     
## [117] "Succinivibrionaceae_UCG-002"                       
## [118] "Desulfobulbus"                                     
## [119] "Fusobacterium"                                     
## [120] "Methanobrevibacter"                                
## [121] "Methanosphaera"                                    
## [122] "Candidatus_Methanomethylophilus"                   
## [123] "Methanocorpusculum"                                
## [124] "Rhodobacter"                                       
## [125] "Ketogulonicigenium"                                
## [126] "Devosia"                                           
## [127] "Sphingomonas"                                      
## [128] "Novosphingobium"                                   
## [129] "Sphingobium"                                       
## [130] "Ochrobactrum"                                      
## [131] "Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium"
## [132] "Neorhizobium"                                      
## [133] "Chelativorans"                                     
## [134] "Methylobacterium"                                  
## [135] "Brevundimonas"                                     
## [136] "Desulfovibrio"                                     
## [137] "Mailhella"                                         
## [138] "Desulfuromonas"                                    
## [139] "M2PT2-76_termite_group"                            
## [140] "Sediminispirochaeta"                               
## [141] "Treponema_2"                                       
## [142] "Pseudoclavibacter"                                 
## [143] "Galbitalea"                                        
## [144] "Frigoribacterium"                                  
## [145] "Sanguibacter"                                      
## [146] "Corynebacterium_1"                                 
## [147] "Corynebacterium"                                   
## [148] "Rhodococcus"                                       
## [149] "Aeromicrobium"                                     
## [150] "Raoultibacter"                                     
## [151] "Denitrobacterium"                                  
## [152] "DNF00809"                                          
## [153] "Slackia"                                           
## [154] "Atopobium"                                         
## [155] "Olsenella"                                         
## [156] "Fibrobacter"                                       
## [157] "Flexilinea"                                        
## [158] "Synergistes"                                       
## [159] "Fretibacterium"                                    
## [160] "Pyramidobacter"                                    
## [161] "Christensenellaceae_R-7_group"                     
## [162] "Ruminococcaceae_UCG-010"                           
## [163] "Prevotellaceae_UCG-003"                            
## [164] "Alloprevotella"                                    
## [165] "Prevotellaceae_UCG-004"                            
## [166] "Prevotellaceae_UCG-001"                            
## [167] "Prevotellaceae_Ga6A1_group"                        
## [168] "Prevotella_1"                                      
## [169] "Prevotellaceae_NK3B31_group"                       
## [170] "Prevotellaceae_YAB2003_group"                      
## [171] "Bacteroides"                                       
## [172] "Rikenellaceae_RC9_gut_group"                       
## [173] "dgA-11_gut_group"                                  
## [174] "U29-B03"                                           
## [175] "Sphingobacterium"                                  
## [176] "Pedobacter"                                        
## [177] "Alistipes"                                         
## [178] "Dyadobacter"                                       
## [179] "Tannerella"                                        
## [180] "Parabacteroides"                                   
## [181] "Porphyromonas"                                     
## [182] "hoa5-07d05_gut_group"                              
## [183] "Ruminiclostridium_6"                               
## [184] "Ruminococcus_1"                                    
## [185] "Angelakisella"                                     
## [186] "Ruminiclostridium"                                 
## [187] "Subdoligranulum"                                   
## [188] "UBA1819"                                           
## [189] "Caproiciproducens"                                 
## [190] "Ruminococcus_2"                                    
## [191] "Ruminococcaceae_UCG-001"                           
## [192] "Ruminiclostridium_5"                               
## [193] "CAG-352"                                           
## [194] "Saccharofermentans"                                
## [195] "Ruminiclostridium_1"                               
## [196] "Ruminococcaceae_UCG-012"                           
## [197] "Ruminococcaceae_UCG-013"                           
## [198] "Ruminococcaceae_UCG-009"                           
## [199] "Ruminococcaceae_NK4A214_group"                     
## [200] "Papillibacter"                                     
## [201] "Ruminococcaceae_UCG-007"                           
## [202] "Ruminococcaceae_V9D2013_group"                     
## [203] "Sporobacter"                                       
## [204] "Ruminococcaceae_UCG-005"                           
## [205] "Ruminococcaceae_UCG-004"                           
## [206] "Oscillibacter"                                     
## [207] "Ruminococcaceae_UCG-002"                           
## [208] "Ruminiclostridium_9"                               
## [209] "Flavonifractor"                                    
## [210] "possible_genus_Sk018"                              
## [211] "probable_genus_10"

These are the 211 genera that are found in both the grab sample and liquid strained samples.

Since we saw that liquid strained samples were distinguished from other rumen samples by Kiritimatiellaeota on the DPCoA we will investigate that further.

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 180 taxa and 68 samples ]
## sample_data() Sample Data:       [ 68 samples by 9 sample variables ]
## tax_table()   Taxonomy Table:    [ 180 taxa by 7 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 180 tips and 179 internal nodes ]
## [1] "Kiritimatiellae_WCHB1-41"

There are 180 ASVs assigned to the phylum Kiritimatiellaeota and these ASVs are only assigned down to the order level. Due to this you won’t find these taxa in the corncob data that was run on genera.

##  [1] Stomach Tube      Stomach Tube      Stomach Tube     
##  [4] Stomach Tube      Stomach Tube      Stomach Tube     
##  [7] Stomach Tube      Stomach Tube      Stomach Tube     
## [10] Stomach Tube      Stomach Tube      Grab Sample      
## [13] Grab Sample       Grab Sample       Grab Sample      
## [16] Grab Sample       Grab Sample       Grab Sample      
## [19] Grab Sample       Grab Sample       Grab Sample      
## [22] Grab Sample       Grab Sample       Liquid Strained  
## [25] Liquid Strained   Liquid Strained   Liquid Strained  
## [28] Liquid Strained   Liquid Strained   Liquid Strained  
## [31] Stomach Tube      Liquid Unstrained Liquid Unstrained
## [34] Liquid Unstrained Liquid Unstrained Liquid Unstrained
## [37] Liquid Unstrained Feces             Feces            
## [40] Feces             Feces             Feces            
## [43] Feces             Feces             Feces            
## [46] Feces             Feces             Feces            
## [49] Feces             Solid             Solid            
## [52] Solid             Solid             Solid            
## [55] Solid             Solid             Solid            
## [58] Solid             Solid             Solid            
## [61] Solid             Liquid Strained   Liquid Strained  
## [64] Liquid Strained   Liquid Strained   Liquid Strained  
## [67] Liquid Unstrained Liquid Unstrained
## 6 Levels: Grab Sample Feces Stomach Tube Liquid Strained ... Liquid Unstrained

The phylum Kiritimatiellaeota is found in all sample types.

There are 180 ASVs assigned to the phylum Kiritimatiellaeota, 17 of these ASVs were significant differentially abundant.

# of significant genera in each family
Var1 Freq
Firmicutes_Lachnospiraceae 25
Firmicutes_Ruminococcaceae 15
Bacteroidetes_Prevotellaceae 6
Firmicutes_Veillonellaceae 5
Proteobacteria_Succinivibrionaceae 5
Firmicutes_Erysipelotrichaceae 4
Firmicutes_Family_XIII 3
Bacteroidetes_Rikenellaceae 2
Proteobacteria_Desulfovibrionaceae 2
Synergistetes_Synergistaceae 2
Actinobacteria_Atopobiaceae 1
Actinobacteria_Coriobacteriales_Incertae_Sedis 1
Actinobacteria_Eggerthellaceae 1
Elusimicrobia_Elusimicrobiaceae 1
Elusimicrobia_Endomicrobiaceae 1
Epsilonbacteraeota_Campylobacteraceae 1
Euryarchaeota_Methanobacteriaceae 1
Firmicutes_Christensenellaceae 1
Firmicutes_Defluviitaleaceae 1
Firmicutes_Eubacteriaceae 1
Firmicutes_Streptococcaceae 1
Planctomycetes_Pirellulaceae 1
Proteobacteria_Burkholderiaceae 1
Proteobacteria_Desulfobulbaceae 1
Proteobacteria_Desulfuromonadaceae 1
Proteobacteria_Pseudomonadaceae 1
Spirochaetes_Spirochaetaceae 1
Tenericutes_Anaeroplasmataceae 1

Here we see again that Prevotellaceae, Lachnospiraceae and Ruminococcaceae to have genera that are the significantly differentially abundant.

Phyla with Significant ASVs
Phylum #Significant ASVs Total ASVs Percent Significant ASVs
Actinobacteria 23 96 23.958333
Bacteroidetes 56 1257 4.455052
Chloroflexi 15 39 38.461539
Cyanobacteria 6 65 9.230769
Elusimicrobia 3 16 18.750000
Euryarchaeota 16 44 36.363636
Fibrobacteres 8 39 20.512821
Firmicutes 540 3095 17.447496
Kiritimatiellaeota 17 180 9.444444
Lentisphaerae 3 31 9.677419
Patescibacteria 3 14 21.428571
Proteobacteria 11 219 5.022831
Spirochaetes 8 138 5.797101
Tenericutes 15 188 7.978723
Verrucomicrobia 1 35 2.857143
Deferribacteres 0 1 0.000000
Epsilonbacteraeota 0 2 0.000000
Fusobacteria 0 4 0.000000
Gemmatimonadetes 0 1 0.000000
Planctomycetes 0 15 0.000000
Synergistetes 0 6 0.000000

We also saw on the DPCoA that a group of Bacteroidetes (Prevotellaceae) was associated with the liquid strained samples. Additionally, another family in the same phylum, Lachnospiraceae, wasn’t associate with liquid strained samples.

As a reminder we can do differential abundance testing on genera and graph all the results from the phylum Bacteroidetes.

We will look further into these families to decipher what genera are causing this difference between grab and liquid samples.

## 
## -1  1 
##  2  4

In the family Prevotellaceae there are 2 genera significantly lower in relative abundance and 4 genera with significantly higher relative abundance in stomach tube compared to grab samples.

x xmin xmax variable Genus
-1.0395575 -1.4609369 -0.6181780 Liquid Strained Differential Abundance Prevotellaceae_NK3B31_group
-0.6891250 -0.9859915 -0.3922586 Liquid Strained Differential Abundance Prevotellaceae_UCG-004
0.8598287 0.7214513 0.9982061 Liquid Strained Differential Abundance Prevotellaceae_UCG-001
1.1682901 0.2628093 2.0737709 Liquid Strained Differential Abundance Prevotellaceae_YAB2003_group
1.1737147 1.0347963 1.3126331 Liquid Strained Differential Abundance Prevotellaceae_UCG-003
1.2715117 1.0897500 1.4532734 Liquid Strained Differential Abundance Prevotella_1

These are the Prevotellaceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.

## 
## -1  1 
##  7  8

In the family Ruminococcaceae there are 7 genera significantly lower in relative abundance and 8 genera with significantly higher relative abundance in stomach tube compared to grab samples.

x xmin xmax variable Genus
-1.3453328 -2.6413920 -0.0492735 Liquid Strained Differential Abundance Caproiciproducens
-1.2056047 -1.3647354 -1.0464741 Liquid Strained Differential Abundance Saccharofermentans
-0.8534209 -1.1680016 -0.5388402 Liquid Strained Differential Abundance Papillibacter
-0.4246426 -0.5459944 -0.3032907 Liquid Strained Differential Abundance Ruminococcus_1
-0.3820756 -0.5860149 -0.1781363 Liquid Strained Differential Abundance Ruminococcaceae_UCG-005
-0.2635253 -0.4265474 -0.1005032 Liquid Strained Differential Abundance Ruminococcaceae_UCG-010
-0.2426040 -0.3496181 -0.1355899 Liquid Strained Differential Abundance Ruminococcaceae_UCG-014
0.2581495 0.1321582 0.3841409 Liquid Strained Differential Abundance Ruminococcaceae_NK4A214_group
0.3558794 0.1207070 0.5910518 Liquid Strained Differential Abundance Ruminococcus_2
0.5051468 0.2751281 0.7351655 Liquid Strained Differential Abundance Ruminococcaceae_UCG-004
0.6982247 0.1210530 1.2753963 Liquid Strained Differential Abundance Ruminococcaceae_UCG-001
0.8095391 0.4188809 1.2001974 Liquid Strained Differential Abundance Ruminiclostridium_9
1.2720314 1.0289351 1.5151278 Liquid Strained Differential Abundance Ruminococcaceae_V9D2013_group
1.6229601 1.2512347 1.9946856 Liquid Strained Differential Abundance Ruminococcaceae_UCG-013
1.7220503 1.3963081 2.0477924 Liquid Strained Differential Abundance Ruminococcaceae_UCG-002

These are the Ruminococcaceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.

## 
## -1  1 
## 22  3

In the family Lachnospiraceae there are 22 genera significantly lower in relative abundance and 3 genera with significantly higher relative abundance in stomach tube compared to grab samples.

x xmin xmax variable Genus
-1.6853162 -2.8561358 -0.5144965 Liquid Strained Differential Abundance Butyrivibrio
-1.5519291 -1.8484651 -1.2553931 Liquid Strained Differential Abundance Lachnoclostridium_10
-1.3151462 -2.3454300 -0.2848623 Liquid Strained Differential Abundance Fusicatenibacter
-1.2927867 -1.7671418 -0.8184316 Liquid Strained Differential Abundance Coprococcus_1
-1.2642825 -1.7307755 -0.7977896 Liquid Strained Differential Abundance Lachnospiraceae_UCG-002
-1.2205535 -2.2914813 -0.1496256 Liquid Strained Differential Abundance Lachnoclostridium
-1.1866044 -1.4115176 -0.9616912 Liquid Strained Differential Abundance probable_genus_10
-1.1721461 -2.0657393 -0.2785528 Liquid Strained Differential Abundance GCA-900066575
-1.1635327 -1.4643447 -0.8627207 Liquid Strained Differential Abundance Lachnospiraceae_UCG-006
-1.1167935 -1.3105063 -0.9230807 Liquid Strained Differential Abundance Lachnospiraceae_NK3A20_group
-1.1059423 -1.7519892 -0.4598953 Liquid Strained Differential Abundance Lachnospiraceae_UCG-010
-1.0858461 -1.3568485 -0.8148437 Liquid Strained Differential Abundance Marvinbryantia
-1.0489392 -1.3258423 -0.7720361 Liquid Strained Differential Abundance Lachnospiraceae_FCS020_group
-0.9668531 -1.2363998 -0.6973064 Liquid Strained Differential Abundance Moryella
-0.9563162 -1.6386116 -0.2740208 Liquid Strained Differential Abundance Lachnospiraceae_FE2018_group
-0.9413635 -1.4029512 -0.4797758 Liquid Strained Differential Abundance Acetatifactor
-0.9388259 -1.0801695 -0.7974823 Liquid Strained Differential Abundance Lachnospiraceae_AC2044_group
-0.8050490 -1.0692876 -0.5408105 Liquid Strained Differential Abundance Lachnospiraceae_UCG-008
-0.4973641 -0.8497914 -0.1449368 Liquid Strained Differential Abundance possible_genus_Sk018
-0.4958562 -0.6231301 -0.3685824 Liquid Strained Differential Abundance Butyrivibrio_2
-0.4777957 -0.6777349 -0.2778565 Liquid Strained Differential Abundance Lachnospiraceae_XPB1014_group
-0.4617096 -0.6778755 -0.2455438 Liquid Strained Differential Abundance Lachnospiraceae_ND3007_group
0.4937215 0.1923139 0.7951290 Liquid Strained Differential Abundance Roseburia
0.7951294 0.3027545 1.2875042 Liquid Strained Differential Abundance Tyzzerella_3
1.8744033 1.2078136 2.5409931 Liquid Strained Differential Abundance Howardella

These are the Lachnospiraceae genera that have are either significantly higher (positive x) or lower (negative x) relative abundance.

Stomach Tube vs Liquid Samples

## [1] "Families in liquid strained samples not in stomach tube"
##  [1] "Incertae_Sedis"     "Terrisporobacter"   "Breznakia"         
##  [4] "Allobaculum"        "Jeotgalicoccus"     "Proteiniclasticum" 
##  [7] "Sarcina"            "Gilvimarinus"       "Pigmentiphaga"     
## [10] "Aestuariispira"     "Methanimicrococcus" "Rhodobacter"       
## [13] "Ketogulonicigenium" "Sphingobium"        "Aureimonas"        
## [16] "Pseudochrobactrum"  "Glutamicibacter"    "Pontibacter"       
## [19] "Sphingobacterium"   "Anaerocella"        "Dyadobacter"       
## [22] "Anaerofilum"        "UBA1819"            "Faecalibacterium"  
## [25] "Oscillibacter"
## [1] "Families in stomach tube samples not in liquid strained samples"
##  [1] "Tyzzerella"               "Cellulosilyticum"        
##  [3] "Filifactor"               "Parvimonas"              
##  [5] "Kandleria"                "Desemzia"                
##  [7] "Alysiella"                "Limnohabitans"           
##  [9] "Leptotrichia"             "Salana"                  
## [11] "Curtobacterium"           "Leucobacter"             
## [13] "Harryflintia"             "Hydrogenoanaerobacterium"
## [1] "Families in liquid unstrained samples not in stomach tube"
##  [1] "Incertae_Sedis"    "Terrisporobacter"  "Paeniclostridium" 
##  [4] "Allobaculum"       "Jeotgalicoccus"    "Peptococcus"      
##  [7] "Proteiniclasticum" "Sarcina"           "Rhodobacter"      
## [10] "Pseudochrobactrum" "GWE2-31-10"        "Kineococcus"      
## [13] "Aeriscardovia"     "Glutamicibacter"   "Sphingobacterium" 
## [16] "Anaerocella"       "Chryseobacterium"  "Gillisia"         
## [19] "Rikenella"         "Dyadobacter"       "Hymenobacter"     
## [22] "Proteiniphilum"    "Negativibacillus"  "Oscillibacter"
## [1] "Families in stomach tube samples not in liquid unstrained samples"
##  [1] "Dorea"            "Filifactor"       "Parvimonas"      
##  [4] "Kandleria"        "Desemzia"         "Jeotgalibaca"    
##  [7] "Aeribacillus"     "Alysiella"        "Caviibacter"     
## [10] "Leptotrichia"     "Ochrobactrum"     "Salana"          
## [13] "Clavibacter"      "Frigoribacterium" "Leucobacter"     
## [16] "Aeromicrobium"    "Slackia"          "Synergistes"     
## [19] "Tannerella"       "Harryflintia"

Looking to see if stomach tubes are much different than liquid samples

Exploratory analysis of DPCoA.

This looks like liquid samples (strained mostly) differ from stomach tube samples in due to increases in Rikenellaceae, Prevotellaceae and Kiritimatiellaeota. Stomach stube samples have an increase in Christensenllaceae and Lachnospiraceae.